Add files using upload-large-folder tool
Browse filesThis view is limited to 50 files because it contains too many changes. See raw diff
- overgeneralisation_original_Swedish/Qwen3.5-4B-Base_overgeneralisation_splits_original_features_train_overgeneralisation_splits_original_features_test1/checkpoint-100/README.md +209 -0
- overgeneralisation_original_Swedish/Qwen3.5-4B-Base_overgeneralisation_splits_original_features_train_overgeneralisation_splits_original_features_test1/checkpoint-100/adapter_config.json +46 -0
- overgeneralisation_original_Swedish/Qwen3.5-4B-Base_overgeneralisation_splits_original_features_train_overgeneralisation_splits_original_features_test1/checkpoint-100/chat_template.jinja +154 -0
- overgeneralisation_original_Swedish/Qwen3.5-4B-Base_overgeneralisation_splits_original_features_train_overgeneralisation_splits_original_features_test1/checkpoint-100/tokenizer_config.json +31 -0
- overgeneralisation_original_Swedish/Qwen3.5-4B-Base_overgeneralisation_splits_original_features_train_overgeneralisation_splits_original_features_test1/checkpoint-100/trainer_state.json +139 -0
- overgeneralisation_original_Swedish/Qwen3.5-4B-Base_overgeneralisation_splits_original_features_train_overgeneralisation_splits_original_features_test1/checkpoint-1000/README.md +209 -0
- overgeneralisation_original_Swedish/Qwen3.5-4B-Base_overgeneralisation_splits_original_features_train_overgeneralisation_splits_original_features_test1/checkpoint-1000/adapter_config.json +46 -0
- overgeneralisation_original_Swedish/Qwen3.5-4B-Base_overgeneralisation_splits_original_features_train_overgeneralisation_splits_original_features_test1/checkpoint-1000/chat_template.jinja +154 -0
- overgeneralisation_original_Swedish/Qwen3.5-4B-Base_overgeneralisation_splits_original_features_train_overgeneralisation_splits_original_features_test1/checkpoint-1000/tokenizer_config.json +31 -0
- overgeneralisation_original_Swedish/Qwen3.5-4B-Base_overgeneralisation_splits_original_features_train_overgeneralisation_splits_original_features_test1/checkpoint-1000/trainer_state.json +1084 -0
- overgeneralisation_original_Swedish/Qwen3.5-4B-Base_overgeneralisation_splits_original_features_train_overgeneralisation_splits_original_features_test1/checkpoint-1020/README.md +209 -0
- overgeneralisation_original_Swedish/Qwen3.5-4B-Base_overgeneralisation_splits_original_features_train_overgeneralisation_splits_original_features_test1/checkpoint-1020/adapter_config.json +46 -0
- overgeneralisation_original_Swedish/Qwen3.5-4B-Base_overgeneralisation_splits_original_features_train_overgeneralisation_splits_original_features_test1/checkpoint-1020/chat_template.jinja +154 -0
- overgeneralisation_original_Swedish/Qwen3.5-4B-Base_overgeneralisation_splits_original_features_train_overgeneralisation_splits_original_features_test1/checkpoint-1020/tokenizer_config.json +31 -0
- overgeneralisation_original_Swedish/Qwen3.5-4B-Base_overgeneralisation_splits_original_features_train_overgeneralisation_splits_original_features_test1/checkpoint-1020/trainer_state.json +1105 -0
- overgeneralisation_original_Swedish/Qwen3.5-4B-Base_overgeneralisation_splits_original_features_train_overgeneralisation_splits_original_features_test1/checkpoint-1040/README.md +209 -0
- overgeneralisation_original_Swedish/Qwen3.5-4B-Base_overgeneralisation_splits_original_features_train_overgeneralisation_splits_original_features_test1/checkpoint-1040/adapter_config.json +46 -0
- overgeneralisation_original_Swedish/Qwen3.5-4B-Base_overgeneralisation_splits_original_features_train_overgeneralisation_splits_original_features_test1/checkpoint-1040/chat_template.jinja +154 -0
- overgeneralisation_original_Swedish/Qwen3.5-4B-Base_overgeneralisation_splits_original_features_train_overgeneralisation_splits_original_features_test1/checkpoint-1040/tokenizer_config.json +31 -0
- overgeneralisation_original_Swedish/Qwen3.5-4B-Base_overgeneralisation_splits_original_features_train_overgeneralisation_splits_original_features_test1/checkpoint-1040/trainer_state.json +1126 -0
- overgeneralisation_original_Swedish/Qwen3.5-4B-Base_overgeneralisation_splits_original_features_train_overgeneralisation_splits_original_features_test1/checkpoint-1060/README.md +209 -0
- overgeneralisation_original_Swedish/Qwen3.5-4B-Base_overgeneralisation_splits_original_features_train_overgeneralisation_splits_original_features_test1/checkpoint-1060/adapter_config.json +46 -0
- overgeneralisation_original_Swedish/Qwen3.5-4B-Base_overgeneralisation_splits_original_features_train_overgeneralisation_splits_original_features_test1/checkpoint-1060/chat_template.jinja +154 -0
- overgeneralisation_original_Swedish/Qwen3.5-4B-Base_overgeneralisation_splits_original_features_train_overgeneralisation_splits_original_features_test1/checkpoint-1060/tokenizer_config.json +31 -0
- overgeneralisation_original_Swedish/Qwen3.5-4B-Base_overgeneralisation_splits_original_features_train_overgeneralisation_splits_original_features_test1/checkpoint-1060/trainer_state.json +1147 -0
- overgeneralisation_original_Swedish/Qwen3.5-4B-Base_overgeneralisation_splits_original_features_train_overgeneralisation_splits_original_features_test1/checkpoint-1080/README.md +209 -0
- overgeneralisation_original_Swedish/Qwen3.5-4B-Base_overgeneralisation_splits_original_features_train_overgeneralisation_splits_original_features_test1/checkpoint-1080/adapter_config.json +46 -0
- overgeneralisation_original_Swedish/Qwen3.5-4B-Base_overgeneralisation_splits_original_features_train_overgeneralisation_splits_original_features_test1/checkpoint-1080/chat_template.jinja +154 -0
- overgeneralisation_original_Swedish/Qwen3.5-4B-Base_overgeneralisation_splits_original_features_train_overgeneralisation_splits_original_features_test1/checkpoint-1080/tokenizer_config.json +31 -0
- overgeneralisation_original_Swedish/Qwen3.5-4B-Base_overgeneralisation_splits_original_features_train_overgeneralisation_splits_original_features_test1/checkpoint-1080/trainer_state.json +1168 -0
- overgeneralisation_original_Swedish/Qwen3.5-4B-Base_overgeneralisation_splits_original_features_train_overgeneralisation_splits_original_features_test1/checkpoint-1100/README.md +209 -0
- overgeneralisation_original_Swedish/Qwen3.5-4B-Base_overgeneralisation_splits_original_features_train_overgeneralisation_splits_original_features_test1/checkpoint-1100/adapter_config.json +46 -0
- overgeneralisation_original_Swedish/Qwen3.5-4B-Base_overgeneralisation_splits_original_features_train_overgeneralisation_splits_original_features_test1/checkpoint-1100/chat_template.jinja +154 -0
- overgeneralisation_original_Swedish/Qwen3.5-4B-Base_overgeneralisation_splits_original_features_train_overgeneralisation_splits_original_features_test1/checkpoint-1100/tokenizer_config.json +31 -0
- overgeneralisation_original_Swedish/Qwen3.5-4B-Base_overgeneralisation_splits_original_features_train_overgeneralisation_splits_original_features_test1/checkpoint-1100/trainer_state.json +1189 -0
- overgeneralisation_original_Swedish/Qwen3.5-4B-Base_overgeneralisation_splits_original_features_train_overgeneralisation_splits_original_features_test1/checkpoint-1120/README.md +209 -0
- overgeneralisation_original_Swedish/Qwen3.5-4B-Base_overgeneralisation_splits_original_features_train_overgeneralisation_splits_original_features_test1/checkpoint-1120/adapter_config.json +46 -0
- overgeneralisation_original_Swedish/Qwen3.5-4B-Base_overgeneralisation_splits_original_features_train_overgeneralisation_splits_original_features_test1/checkpoint-1120/chat_template.jinja +154 -0
- overgeneralisation_original_Swedish/Qwen3.5-4B-Base_overgeneralisation_splits_original_features_train_overgeneralisation_splits_original_features_test1/checkpoint-1120/tokenizer_config.json +31 -0
- overgeneralisation_original_Swedish/Qwen3.5-4B-Base_overgeneralisation_splits_original_features_train_overgeneralisation_splits_original_features_test1/checkpoint-1120/trainer_state.json +1210 -0
- overgeneralisation_original_Swedish/Qwen3.5-4B-Base_overgeneralisation_splits_original_features_train_overgeneralisation_splits_original_features_test1/checkpoint-1140/README.md +209 -0
- overgeneralisation_original_Swedish/Qwen3.5-4B-Base_overgeneralisation_splits_original_features_train_overgeneralisation_splits_original_features_test1/checkpoint-1140/adapter_config.json +46 -0
- overgeneralisation_original_Swedish/Qwen3.5-4B-Base_overgeneralisation_splits_original_features_train_overgeneralisation_splits_original_features_test1/checkpoint-1140/chat_template.jinja +154 -0
- overgeneralisation_original_Swedish/Qwen3.5-4B-Base_overgeneralisation_splits_original_features_train_overgeneralisation_splits_original_features_test1/checkpoint-1140/tokenizer_config.json +31 -0
- overgeneralisation_original_Swedish/Qwen3.5-4B-Base_overgeneralisation_splits_original_features_train_overgeneralisation_splits_original_features_test1/checkpoint-1140/trainer_state.json +1231 -0
- overgeneralisation_original_Swedish/Qwen3.5-4B-Base_overgeneralisation_splits_original_features_train_overgeneralisation_splits_original_features_test1/checkpoint-1160/README.md +209 -0
- overgeneralisation_original_Swedish/Qwen3.5-4B-Base_overgeneralisation_splits_original_features_train_overgeneralisation_splits_original_features_test1/checkpoint-1160/adapter_config.json +46 -0
- overgeneralisation_original_Swedish/Qwen3.5-4B-Base_overgeneralisation_splits_original_features_train_overgeneralisation_splits_original_features_test1/checkpoint-1160/chat_template.jinja +154 -0
- overgeneralisation_original_Swedish/Qwen3.5-4B-Base_overgeneralisation_splits_original_features_train_overgeneralisation_splits_original_features_test1/checkpoint-1160/tokenizer_config.json +31 -0
- overgeneralisation_original_Swedish/Qwen3.5-4B-Base_overgeneralisation_splits_original_features_train_overgeneralisation_splits_original_features_test1/checkpoint-1160/trainer_state.json +1252 -0
overgeneralisation_original_Swedish/Qwen3.5-4B-Base_overgeneralisation_splits_original_features_train_overgeneralisation_splits_original_features_test1/checkpoint-100/README.md
ADDED
|
@@ -0,0 +1,209 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
---
|
| 2 |
+
base_model: Qwen/Qwen3.5-4B-Base
|
| 3 |
+
library_name: peft
|
| 4 |
+
pipeline_tag: text-generation
|
| 5 |
+
tags:
|
| 6 |
+
- base_model:adapter:Qwen/Qwen3.5-4B-Base
|
| 7 |
+
- lora
|
| 8 |
+
- sft
|
| 9 |
+
- transformers
|
| 10 |
+
- trl
|
| 11 |
+
---
|
| 12 |
+
|
| 13 |
+
# Model Card for Model ID
|
| 14 |
+
|
| 15 |
+
<!-- Provide a quick summary of what the model is/does. -->
|
| 16 |
+
|
| 17 |
+
|
| 18 |
+
|
| 19 |
+
## Model Details
|
| 20 |
+
|
| 21 |
+
### Model Description
|
| 22 |
+
|
| 23 |
+
<!-- Provide a longer summary of what this model is. -->
|
| 24 |
+
|
| 25 |
+
|
| 26 |
+
|
| 27 |
+
- **Developed by:** [More Information Needed]
|
| 28 |
+
- **Funded by [optional]:** [More Information Needed]
|
| 29 |
+
- **Shared by [optional]:** [More Information Needed]
|
| 30 |
+
- **Model type:** [More Information Needed]
|
| 31 |
+
- **Language(s) (NLP):** [More Information Needed]
|
| 32 |
+
- **License:** [More Information Needed]
|
| 33 |
+
- **Finetuned from model [optional]:** [More Information Needed]
|
| 34 |
+
|
| 35 |
+
### Model Sources [optional]
|
| 36 |
+
|
| 37 |
+
<!-- Provide the basic links for the model. -->
|
| 38 |
+
|
| 39 |
+
- **Repository:** [More Information Needed]
|
| 40 |
+
- **Paper [optional]:** [More Information Needed]
|
| 41 |
+
- **Demo [optional]:** [More Information Needed]
|
| 42 |
+
|
| 43 |
+
## Uses
|
| 44 |
+
|
| 45 |
+
<!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
|
| 46 |
+
|
| 47 |
+
### Direct Use
|
| 48 |
+
|
| 49 |
+
<!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
|
| 50 |
+
|
| 51 |
+
[More Information Needed]
|
| 52 |
+
|
| 53 |
+
### Downstream Use [optional]
|
| 54 |
+
|
| 55 |
+
<!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
|
| 56 |
+
|
| 57 |
+
[More Information Needed]
|
| 58 |
+
|
| 59 |
+
### Out-of-Scope Use
|
| 60 |
+
|
| 61 |
+
<!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
|
| 62 |
+
|
| 63 |
+
[More Information Needed]
|
| 64 |
+
|
| 65 |
+
## Bias, Risks, and Limitations
|
| 66 |
+
|
| 67 |
+
<!-- This section is meant to convey both technical and sociotechnical limitations. -->
|
| 68 |
+
|
| 69 |
+
[More Information Needed]
|
| 70 |
+
|
| 71 |
+
### Recommendations
|
| 72 |
+
|
| 73 |
+
<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
|
| 74 |
+
|
| 75 |
+
Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
|
| 76 |
+
|
| 77 |
+
## How to Get Started with the Model
|
| 78 |
+
|
| 79 |
+
Use the code below to get started with the model.
|
| 80 |
+
|
| 81 |
+
[More Information Needed]
|
| 82 |
+
|
| 83 |
+
## Training Details
|
| 84 |
+
|
| 85 |
+
### Training Data
|
| 86 |
+
|
| 87 |
+
<!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
|
| 88 |
+
|
| 89 |
+
[More Information Needed]
|
| 90 |
+
|
| 91 |
+
### Training Procedure
|
| 92 |
+
|
| 93 |
+
<!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
|
| 94 |
+
|
| 95 |
+
#### Preprocessing [optional]
|
| 96 |
+
|
| 97 |
+
[More Information Needed]
|
| 98 |
+
|
| 99 |
+
|
| 100 |
+
#### Training Hyperparameters
|
| 101 |
+
|
| 102 |
+
- **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
|
| 103 |
+
|
| 104 |
+
#### Speeds, Sizes, Times [optional]
|
| 105 |
+
|
| 106 |
+
<!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
|
| 107 |
+
|
| 108 |
+
[More Information Needed]
|
| 109 |
+
|
| 110 |
+
## Evaluation
|
| 111 |
+
|
| 112 |
+
<!-- This section describes the evaluation protocols and provides the results. -->
|
| 113 |
+
|
| 114 |
+
### Testing Data, Factors & Metrics
|
| 115 |
+
|
| 116 |
+
#### Testing Data
|
| 117 |
+
|
| 118 |
+
<!-- This should link to a Dataset Card if possible. -->
|
| 119 |
+
|
| 120 |
+
[More Information Needed]
|
| 121 |
+
|
| 122 |
+
#### Factors
|
| 123 |
+
|
| 124 |
+
<!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
|
| 125 |
+
|
| 126 |
+
[More Information Needed]
|
| 127 |
+
|
| 128 |
+
#### Metrics
|
| 129 |
+
|
| 130 |
+
<!-- These are the evaluation metrics being used, ideally with a description of why. -->
|
| 131 |
+
|
| 132 |
+
[More Information Needed]
|
| 133 |
+
|
| 134 |
+
### Results
|
| 135 |
+
|
| 136 |
+
[More Information Needed]
|
| 137 |
+
|
| 138 |
+
#### Summary
|
| 139 |
+
|
| 140 |
+
|
| 141 |
+
|
| 142 |
+
## Model Examination [optional]
|
| 143 |
+
|
| 144 |
+
<!-- Relevant interpretability work for the model goes here -->
|
| 145 |
+
|
| 146 |
+
[More Information Needed]
|
| 147 |
+
|
| 148 |
+
## Environmental Impact
|
| 149 |
+
|
| 150 |
+
<!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
|
| 151 |
+
|
| 152 |
+
Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
|
| 153 |
+
|
| 154 |
+
- **Hardware Type:** [More Information Needed]
|
| 155 |
+
- **Hours used:** [More Information Needed]
|
| 156 |
+
- **Cloud Provider:** [More Information Needed]
|
| 157 |
+
- **Compute Region:** [More Information Needed]
|
| 158 |
+
- **Carbon Emitted:** [More Information Needed]
|
| 159 |
+
|
| 160 |
+
## Technical Specifications [optional]
|
| 161 |
+
|
| 162 |
+
### Model Architecture and Objective
|
| 163 |
+
|
| 164 |
+
[More Information Needed]
|
| 165 |
+
|
| 166 |
+
### Compute Infrastructure
|
| 167 |
+
|
| 168 |
+
[More Information Needed]
|
| 169 |
+
|
| 170 |
+
#### Hardware
|
| 171 |
+
|
| 172 |
+
[More Information Needed]
|
| 173 |
+
|
| 174 |
+
#### Software
|
| 175 |
+
|
| 176 |
+
[More Information Needed]
|
| 177 |
+
|
| 178 |
+
## Citation [optional]
|
| 179 |
+
|
| 180 |
+
<!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
|
| 181 |
+
|
| 182 |
+
**BibTeX:**
|
| 183 |
+
|
| 184 |
+
[More Information Needed]
|
| 185 |
+
|
| 186 |
+
**APA:**
|
| 187 |
+
|
| 188 |
+
[More Information Needed]
|
| 189 |
+
|
| 190 |
+
## Glossary [optional]
|
| 191 |
+
|
| 192 |
+
<!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
|
| 193 |
+
|
| 194 |
+
[More Information Needed]
|
| 195 |
+
|
| 196 |
+
## More Information [optional]
|
| 197 |
+
|
| 198 |
+
[More Information Needed]
|
| 199 |
+
|
| 200 |
+
## Model Card Authors [optional]
|
| 201 |
+
|
| 202 |
+
[More Information Needed]
|
| 203 |
+
|
| 204 |
+
## Model Card Contact
|
| 205 |
+
|
| 206 |
+
[More Information Needed]
|
| 207 |
+
### Framework versions
|
| 208 |
+
|
| 209 |
+
- PEFT 0.18.1
|
overgeneralisation_original_Swedish/Qwen3.5-4B-Base_overgeneralisation_splits_original_features_train_overgeneralisation_splits_original_features_test1/checkpoint-100/adapter_config.json
ADDED
|
@@ -0,0 +1,46 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
{
|
| 2 |
+
"alora_invocation_tokens": null,
|
| 3 |
+
"alpha_pattern": {},
|
| 4 |
+
"arrow_config": null,
|
| 5 |
+
"auto_mapping": null,
|
| 6 |
+
"base_model_name_or_path": "Qwen/Qwen3.5-4B-Base",
|
| 7 |
+
"bias": "none",
|
| 8 |
+
"corda_config": null,
|
| 9 |
+
"ensure_weight_tying": false,
|
| 10 |
+
"eva_config": null,
|
| 11 |
+
"exclude_modules": null,
|
| 12 |
+
"fan_in_fan_out": false,
|
| 13 |
+
"inference_mode": true,
|
| 14 |
+
"init_lora_weights": true,
|
| 15 |
+
"layer_replication": null,
|
| 16 |
+
"layers_pattern": null,
|
| 17 |
+
"layers_to_transform": null,
|
| 18 |
+
"loftq_config": {},
|
| 19 |
+
"lora_alpha": 256,
|
| 20 |
+
"lora_bias": false,
|
| 21 |
+
"lora_dropout": 0.0005183818805460705,
|
| 22 |
+
"megatron_config": null,
|
| 23 |
+
"megatron_core": "megatron.core",
|
| 24 |
+
"modules_to_save": null,
|
| 25 |
+
"peft_type": "LORA",
|
| 26 |
+
"peft_version": "0.18.1",
|
| 27 |
+
"qalora_group_size": 16,
|
| 28 |
+
"r": 128,
|
| 29 |
+
"rank_pattern": {},
|
| 30 |
+
"revision": null,
|
| 31 |
+
"target_modules": [
|
| 32 |
+
"up_proj",
|
| 33 |
+
"q_proj",
|
| 34 |
+
"o_proj",
|
| 35 |
+
"v_proj",
|
| 36 |
+
"k_proj",
|
| 37 |
+
"gate_proj",
|
| 38 |
+
"down_proj"
|
| 39 |
+
],
|
| 40 |
+
"target_parameters": null,
|
| 41 |
+
"task_type": "CAUSAL_LM",
|
| 42 |
+
"trainable_token_indices": null,
|
| 43 |
+
"use_dora": false,
|
| 44 |
+
"use_qalora": false,
|
| 45 |
+
"use_rslora": false
|
| 46 |
+
}
|
overgeneralisation_original_Swedish/Qwen3.5-4B-Base_overgeneralisation_splits_original_features_train_overgeneralisation_splits_original_features_test1/checkpoint-100/chat_template.jinja
ADDED
|
@@ -0,0 +1,154 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
{%- set image_count = namespace(value=0) %}
|
| 2 |
+
{%- set video_count = namespace(value=0) %}
|
| 3 |
+
{%- macro render_content(content, do_vision_count, is_system_content=false) %}
|
| 4 |
+
{%- if content is string %}
|
| 5 |
+
{{- content }}
|
| 6 |
+
{%- elif content is iterable and content is not mapping %}
|
| 7 |
+
{%- for item in content %}
|
| 8 |
+
{%- if 'image' in item or 'image_url' in item or item.type == 'image' %}
|
| 9 |
+
{%- if is_system_content %}
|
| 10 |
+
{{- raise_exception('System message cannot contain images.') }}
|
| 11 |
+
{%- endif %}
|
| 12 |
+
{%- if do_vision_count %}
|
| 13 |
+
{%- set image_count.value = image_count.value + 1 %}
|
| 14 |
+
{%- endif %}
|
| 15 |
+
{%- if add_vision_id %}
|
| 16 |
+
{{- 'Picture ' ~ image_count.value ~ ': ' }}
|
| 17 |
+
{%- endif %}
|
| 18 |
+
{{- '<|vision_start|><|image_pad|><|vision_end|>' }}
|
| 19 |
+
{%- elif 'video' in item or item.type == 'video' %}
|
| 20 |
+
{%- if is_system_content %}
|
| 21 |
+
{{- raise_exception('System message cannot contain videos.') }}
|
| 22 |
+
{%- endif %}
|
| 23 |
+
{%- if do_vision_count %}
|
| 24 |
+
{%- set video_count.value = video_count.value + 1 %}
|
| 25 |
+
{%- endif %}
|
| 26 |
+
{%- if add_vision_id %}
|
| 27 |
+
{{- 'Video ' ~ video_count.value ~ ': ' }}
|
| 28 |
+
{%- endif %}
|
| 29 |
+
{{- '<|vision_start|><|video_pad|><|vision_end|>' }}
|
| 30 |
+
{%- elif 'text' in item %}
|
| 31 |
+
{{- item.text }}
|
| 32 |
+
{%- else %}
|
| 33 |
+
{{- raise_exception('Unexpected item type in content.') }}
|
| 34 |
+
{%- endif %}
|
| 35 |
+
{%- endfor %}
|
| 36 |
+
{%- elif content is none or content is undefined %}
|
| 37 |
+
{{- '' }}
|
| 38 |
+
{%- else %}
|
| 39 |
+
{{- raise_exception('Unexpected content type.') }}
|
| 40 |
+
{%- endif %}
|
| 41 |
+
{%- endmacro %}
|
| 42 |
+
{%- if not messages %}
|
| 43 |
+
{{- raise_exception('No messages provided.') }}
|
| 44 |
+
{%- endif %}
|
| 45 |
+
{%- if tools and tools is iterable and tools is not mapping %}
|
| 46 |
+
{{- '<|im_start|>system\n' }}
|
| 47 |
+
{{- "# Tools\n\nYou have access to the following functions:\n\n<tools>" }}
|
| 48 |
+
{%- for tool in tools %}
|
| 49 |
+
{{- "\n" }}
|
| 50 |
+
{{- tool | tojson }}
|
| 51 |
+
{%- endfor %}
|
| 52 |
+
{{- "\n</tools>" }}
|
| 53 |
+
{{- '\n\nIf you choose to call a function ONLY reply in the following format with NO suffix:\n\n<tool_call>\n<function=example_function_name>\n<parameter=example_parameter_1>\nvalue_1\n</parameter>\n<parameter=example_parameter_2>\nThis is the value for the second parameter\nthat can span\nmultiple lines\n</parameter>\n</function>\n</tool_call>\n\n<IMPORTANT>\nReminder:\n- Function calls MUST follow the specified format: an inner <function=...></function> block must be nested within <tool_call></tool_call> XML tags\n- Required parameters MUST be specified\n- You may provide optional reasoning for your function call in natural language BEFORE the function call, but NOT after\n- If there is no function call available, answer the question like normal with your current knowledge and do not tell the user about function calls\n</IMPORTANT>' }}
|
| 54 |
+
{%- if messages[0].role == 'system' %}
|
| 55 |
+
{%- set content = render_content(messages[0].content, false, true)|trim %}
|
| 56 |
+
{%- if content %}
|
| 57 |
+
{{- '\n\n' + content }}
|
| 58 |
+
{%- endif %}
|
| 59 |
+
{%- endif %}
|
| 60 |
+
{{- '<|im_end|>\n' }}
|
| 61 |
+
{%- else %}
|
| 62 |
+
{%- if messages[0].role == 'system' %}
|
| 63 |
+
{%- set content = render_content(messages[0].content, false, true)|trim %}
|
| 64 |
+
{{- '<|im_start|>system\n' + content + '<|im_end|>\n' }}
|
| 65 |
+
{%- endif %}
|
| 66 |
+
{%- endif %}
|
| 67 |
+
{%- set ns = namespace(multi_step_tool=true, last_query_index=messages|length - 1) %}
|
| 68 |
+
{%- for message in messages[::-1] %}
|
| 69 |
+
{%- set index = (messages|length - 1) - loop.index0 %}
|
| 70 |
+
{%- if ns.multi_step_tool and message.role == "user" %}
|
| 71 |
+
{%- set content = render_content(message.content, false)|trim %}
|
| 72 |
+
{%- if not(content.startswith('<tool_response>') and content.endswith('</tool_response>')) %}
|
| 73 |
+
{%- set ns.multi_step_tool = false %}
|
| 74 |
+
{%- set ns.last_query_index = index %}
|
| 75 |
+
{%- endif %}
|
| 76 |
+
{%- endif %}
|
| 77 |
+
{%- endfor %}
|
| 78 |
+
{%- if ns.multi_step_tool %}
|
| 79 |
+
{{- raise_exception('No user query found in messages.') }}
|
| 80 |
+
{%- endif %}
|
| 81 |
+
{%- for message in messages %}
|
| 82 |
+
{%- set content = render_content(message.content, true)|trim %}
|
| 83 |
+
{%- if message.role == "system" %}
|
| 84 |
+
{%- if not loop.first %}
|
| 85 |
+
{{- raise_exception('System message must be at the beginning.') }}
|
| 86 |
+
{%- endif %}
|
| 87 |
+
{%- elif message.role == "user" %}
|
| 88 |
+
{{- '<|im_start|>' + message.role + '\n' + content + '<|im_end|>' + '\n' }}
|
| 89 |
+
{%- elif message.role == "assistant" %}
|
| 90 |
+
{%- set reasoning_content = '' %}
|
| 91 |
+
{%- if message.reasoning_content is string %}
|
| 92 |
+
{%- set reasoning_content = message.reasoning_content %}
|
| 93 |
+
{%- else %}
|
| 94 |
+
{%- if '</think>' in content %}
|
| 95 |
+
{%- set reasoning_content = content.split('</think>')[0].rstrip('\n').split('<think>')[-1].lstrip('\n') %}
|
| 96 |
+
{%- set content = content.split('</think>')[-1].lstrip('\n') %}
|
| 97 |
+
{%- endif %}
|
| 98 |
+
{%- endif %}
|
| 99 |
+
{%- set reasoning_content = reasoning_content|trim %}
|
| 100 |
+
{%- if loop.index0 > ns.last_query_index %}
|
| 101 |
+
{{- '<|im_start|>' + message.role + '\n<think>\n' + reasoning_content + '\n</think>\n\n' + content }}
|
| 102 |
+
{%- else %}
|
| 103 |
+
{{- '<|im_start|>' + message.role + '\n' + content }}
|
| 104 |
+
{%- endif %}
|
| 105 |
+
{%- if message.tool_calls and message.tool_calls is iterable and message.tool_calls is not mapping %}
|
| 106 |
+
{%- for tool_call in message.tool_calls %}
|
| 107 |
+
{%- if tool_call.function is defined %}
|
| 108 |
+
{%- set tool_call = tool_call.function %}
|
| 109 |
+
{%- endif %}
|
| 110 |
+
{%- if loop.first %}
|
| 111 |
+
{%- if content|trim %}
|
| 112 |
+
{{- '\n\n<tool_call>\n<function=' + tool_call.name + '>\n' }}
|
| 113 |
+
{%- else %}
|
| 114 |
+
{{- '<tool_call>\n<function=' + tool_call.name + '>\n' }}
|
| 115 |
+
{%- endif %}
|
| 116 |
+
{%- else %}
|
| 117 |
+
{{- '\n<tool_call>\n<function=' + tool_call.name + '>\n' }}
|
| 118 |
+
{%- endif %}
|
| 119 |
+
{%- if tool_call.arguments is defined %}
|
| 120 |
+
{%- for args_name, args_value in tool_call.arguments|items %}
|
| 121 |
+
{{- '<parameter=' + args_name + '>\n' }}
|
| 122 |
+
{%- set args_value = args_value | tojson | safe if args_value is mapping or (args_value is sequence and args_value is not string) else args_value | string %}
|
| 123 |
+
{{- args_value }}
|
| 124 |
+
{{- '\n</parameter>\n' }}
|
| 125 |
+
{%- endfor %}
|
| 126 |
+
{%- endif %}
|
| 127 |
+
{{- '</function>\n</tool_call>' }}
|
| 128 |
+
{%- endfor %}
|
| 129 |
+
{%- endif %}
|
| 130 |
+
{{- '<|im_end|>\n' }}
|
| 131 |
+
{%- elif message.role == "tool" %}
|
| 132 |
+
{%- if loop.previtem and loop.previtem.role != "tool" %}
|
| 133 |
+
{{- '<|im_start|>user' }}
|
| 134 |
+
{%- endif %}
|
| 135 |
+
{{- '\n<tool_response>\n' }}
|
| 136 |
+
{{- content }}
|
| 137 |
+
{{- '\n</tool_response>' }}
|
| 138 |
+
{%- if not loop.last and loop.nextitem.role != "tool" %}
|
| 139 |
+
{{- '<|im_end|>\n' }}
|
| 140 |
+
{%- elif loop.last %}
|
| 141 |
+
{{- '<|im_end|>\n' }}
|
| 142 |
+
{%- endif %}
|
| 143 |
+
{%- else %}
|
| 144 |
+
{{- raise_exception('Unexpected message role.') }}
|
| 145 |
+
{%- endif %}
|
| 146 |
+
{%- endfor %}
|
| 147 |
+
{%- if add_generation_prompt %}
|
| 148 |
+
{{- '<|im_start|>assistant\n' }}
|
| 149 |
+
{%- if enable_thinking is defined and enable_thinking is false %}
|
| 150 |
+
{{- '<think>\n\n</think>\n\n' }}
|
| 151 |
+
{%- else %}
|
| 152 |
+
{{- '<think>\n' }}
|
| 153 |
+
{%- endif %}
|
| 154 |
+
{%- endif %}
|
overgeneralisation_original_Swedish/Qwen3.5-4B-Base_overgeneralisation_splits_original_features_train_overgeneralisation_splits_original_features_test1/checkpoint-100/tokenizer_config.json
ADDED
|
@@ -0,0 +1,31 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
{
|
| 2 |
+
"add_prefix_space": false,
|
| 3 |
+
"audio_bos_token": "<|audio_start|>",
|
| 4 |
+
"audio_eos_token": "<|audio_end|>",
|
| 5 |
+
"audio_token": "<|audio_pad|>",
|
| 6 |
+
"backend": "tokenizers",
|
| 7 |
+
"bos_token": null,
|
| 8 |
+
"clean_up_tokenization_spaces": false,
|
| 9 |
+
"eos_token": "<|endoftext|>",
|
| 10 |
+
"errors": "replace",
|
| 11 |
+
"image_token": "<|image_pad|>",
|
| 12 |
+
"is_local": false,
|
| 13 |
+
"model_max_length": 262144,
|
| 14 |
+
"model_specific_special_tokens": {
|
| 15 |
+
"audio_bos_token": "<|audio_start|>",
|
| 16 |
+
"audio_eos_token": "<|audio_end|>",
|
| 17 |
+
"audio_token": "<|audio_pad|>",
|
| 18 |
+
"image_token": "<|image_pad|>",
|
| 19 |
+
"video_token": "<|video_pad|>",
|
| 20 |
+
"vision_bos_token": "<|vision_start|>",
|
| 21 |
+
"vision_eos_token": "<|vision_end|>"
|
| 22 |
+
},
|
| 23 |
+
"pad_token": "<|endoftext|>",
|
| 24 |
+
"pretokenize_regex": "(?i:'s|'t|'re|'ve|'m|'ll|'d)|[^\\r\\n\\p{L}\\p{N}]?[\\p{L}\\p{M}]+|\\p{N}| ?[^\\s\\p{L}\\p{M}\\p{N}]+[\\r\\n]*|\\s*[\\r\\n]+|\\s+(?!\\S)|\\s+",
|
| 25 |
+
"split_special_tokens": false,
|
| 26 |
+
"tokenizer_class": "TokenizersBackend",
|
| 27 |
+
"unk_token": null,
|
| 28 |
+
"video_token": "<|video_pad|>",
|
| 29 |
+
"vision_bos_token": "<|vision_start|>",
|
| 30 |
+
"vision_eos_token": "<|vision_end|>"
|
| 31 |
+
}
|
overgeneralisation_original_Swedish/Qwen3.5-4B-Base_overgeneralisation_splits_original_features_train_overgeneralisation_splits_original_features_test1/checkpoint-100/trainer_state.json
ADDED
|
@@ -0,0 +1,139 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
{
|
| 2 |
+
"best_global_step": null,
|
| 3 |
+
"best_metric": null,
|
| 4 |
+
"best_model_checkpoint": null,
|
| 5 |
+
"epoch": 0.24906600249066002,
|
| 6 |
+
"eval_steps": 20,
|
| 7 |
+
"global_step": 100,
|
| 8 |
+
"is_hyper_param_search": false,
|
| 9 |
+
"is_local_process_zero": true,
|
| 10 |
+
"is_world_process_zero": true,
|
| 11 |
+
"log_history": [
|
| 12 |
+
{
|
| 13 |
+
"entropy": 1.9784346982836722,
|
| 14 |
+
"epoch": 0.049813200498132,
|
| 15 |
+
"grad_norm": 3.0229668617248535,
|
| 16 |
+
"learning_rate": 9.526142962415369e-06,
|
| 17 |
+
"loss": 1.7360023498535155,
|
| 18 |
+
"mean_token_accuracy": 0.6449888605624438,
|
| 19 |
+
"num_tokens": 46794.0,
|
| 20 |
+
"step": 20
|
| 21 |
+
},
|
| 22 |
+
{
|
| 23 |
+
"epoch": 0.049813200498132,
|
| 24 |
+
"eval_entropy": 1.41506897571475,
|
| 25 |
+
"eval_loss": 1.1876318454742432,
|
| 26 |
+
"eval_mean_token_accuracy": 0.734131895525511,
|
| 27 |
+
"eval_num_tokens": 46794.0,
|
| 28 |
+
"eval_runtime": 87.8071,
|
| 29 |
+
"eval_samples_per_second": 15.671,
|
| 30 |
+
"eval_steps_per_second": 1.959,
|
| 31 |
+
"step": 20
|
| 32 |
+
},
|
| 33 |
+
{
|
| 34 |
+
"entropy": 1.049924298375845,
|
| 35 |
+
"epoch": 0.099626400996264,
|
| 36 |
+
"grad_norm": 1.5795097351074219,
|
| 37 |
+
"learning_rate": 1.9553661870221022e-05,
|
| 38 |
+
"loss": 0.8944448471069336,
|
| 39 |
+
"mean_token_accuracy": 0.7748479396104813,
|
| 40 |
+
"num_tokens": 90754.0,
|
| 41 |
+
"step": 40
|
| 42 |
+
},
|
| 43 |
+
{
|
| 44 |
+
"epoch": 0.099626400996264,
|
| 45 |
+
"eval_entropy": 0.7996658658565476,
|
| 46 |
+
"eval_loss": 0.7202735543251038,
|
| 47 |
+
"eval_mean_token_accuracy": 0.8070558306089667,
|
| 48 |
+
"eval_num_tokens": 90754.0,
|
| 49 |
+
"eval_runtime": 86.9199,
|
| 50 |
+
"eval_samples_per_second": 15.831,
|
| 51 |
+
"eval_steps_per_second": 1.979,
|
| 52 |
+
"step": 40
|
| 53 |
+
},
|
| 54 |
+
{
|
| 55 |
+
"entropy": 0.7734908878803253,
|
| 56 |
+
"epoch": 0.149439601494396,
|
| 57 |
+
"grad_norm": 1.3136248588562012,
|
| 58 |
+
"learning_rate": 2.9581180778026673e-05,
|
| 59 |
+
"loss": 0.6780608654022217,
|
| 60 |
+
"mean_token_accuracy": 0.8168170280754566,
|
| 61 |
+
"num_tokens": 137472.0,
|
| 62 |
+
"step": 60
|
| 63 |
+
},
|
| 64 |
+
{
|
| 65 |
+
"epoch": 0.149439601494396,
|
| 66 |
+
"eval_entropy": 0.7119324009778888,
|
| 67 |
+
"eval_loss": 0.6554311513900757,
|
| 68 |
+
"eval_mean_token_accuracy": 0.8215604798738346,
|
| 69 |
+
"eval_num_tokens": 137472.0,
|
| 70 |
+
"eval_runtime": 86.8692,
|
| 71 |
+
"eval_samples_per_second": 15.84,
|
| 72 |
+
"eval_steps_per_second": 1.98,
|
| 73 |
+
"step": 60
|
| 74 |
+
},
|
| 75 |
+
{
|
| 76 |
+
"entropy": 0.7071127541363239,
|
| 77 |
+
"epoch": 0.199252801992528,
|
| 78 |
+
"grad_norm": 1.387060284614563,
|
| 79 |
+
"learning_rate": 3.960869968583232e-05,
|
| 80 |
+
"loss": 0.6382100582122803,
|
| 81 |
+
"mean_token_accuracy": 0.8229366384446621,
|
| 82 |
+
"num_tokens": 187408.0,
|
| 83 |
+
"step": 80
|
| 84 |
+
},
|
| 85 |
+
{
|
| 86 |
+
"epoch": 0.199252801992528,
|
| 87 |
+
"eval_entropy": 0.6883931482254073,
|
| 88 |
+
"eval_loss": 0.625065803527832,
|
| 89 |
+
"eval_mean_token_accuracy": 0.828940509710201,
|
| 90 |
+
"eval_num_tokens": 187408.0,
|
| 91 |
+
"eval_runtime": 86.662,
|
| 92 |
+
"eval_samples_per_second": 15.878,
|
| 93 |
+
"eval_steps_per_second": 1.985,
|
| 94 |
+
"step": 80
|
| 95 |
+
},
|
| 96 |
+
{
|
| 97 |
+
"entropy": 0.6800824083387852,
|
| 98 |
+
"epoch": 0.24906600249066002,
|
| 99 |
+
"grad_norm": 0.9892916679382324,
|
| 100 |
+
"learning_rate": 4.963621859363797e-05,
|
| 101 |
+
"loss": 0.6011715888977051,
|
| 102 |
+
"mean_token_accuracy": 0.8323964163661003,
|
| 103 |
+
"num_tokens": 234197.0,
|
| 104 |
+
"step": 100
|
| 105 |
+
},
|
| 106 |
+
{
|
| 107 |
+
"epoch": 0.24906600249066002,
|
| 108 |
+
"eval_entropy": 0.6840810470802839,
|
| 109 |
+
"eval_loss": 0.6037028431892395,
|
| 110 |
+
"eval_mean_token_accuracy": 0.8309669033732525,
|
| 111 |
+
"eval_num_tokens": 234197.0,
|
| 112 |
+
"eval_runtime": 86.4637,
|
| 113 |
+
"eval_samples_per_second": 15.914,
|
| 114 |
+
"eval_steps_per_second": 1.989,
|
| 115 |
+
"step": 100
|
| 116 |
+
}
|
| 117 |
+
],
|
| 118 |
+
"logging_steps": 20,
|
| 119 |
+
"max_steps": 4020,
|
| 120 |
+
"num_input_tokens_seen": 0,
|
| 121 |
+
"num_train_epochs": 10,
|
| 122 |
+
"save_steps": 20,
|
| 123 |
+
"stateful_callbacks": {
|
| 124 |
+
"TrainerControl": {
|
| 125 |
+
"args": {
|
| 126 |
+
"should_epoch_stop": false,
|
| 127 |
+
"should_evaluate": false,
|
| 128 |
+
"should_log": false,
|
| 129 |
+
"should_save": true,
|
| 130 |
+
"should_training_stop": false
|
| 131 |
+
},
|
| 132 |
+
"attributes": {}
|
| 133 |
+
}
|
| 134 |
+
},
|
| 135 |
+
"total_flos": 9823576763965440.0,
|
| 136 |
+
"train_batch_size": 4,
|
| 137 |
+
"trial_name": null,
|
| 138 |
+
"trial_params": null
|
| 139 |
+
}
|
overgeneralisation_original_Swedish/Qwen3.5-4B-Base_overgeneralisation_splits_original_features_train_overgeneralisation_splits_original_features_test1/checkpoint-1000/README.md
ADDED
|
@@ -0,0 +1,209 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
---
|
| 2 |
+
base_model: Qwen/Qwen3.5-4B-Base
|
| 3 |
+
library_name: peft
|
| 4 |
+
pipeline_tag: text-generation
|
| 5 |
+
tags:
|
| 6 |
+
- base_model:adapter:Qwen/Qwen3.5-4B-Base
|
| 7 |
+
- lora
|
| 8 |
+
- sft
|
| 9 |
+
- transformers
|
| 10 |
+
- trl
|
| 11 |
+
---
|
| 12 |
+
|
| 13 |
+
# Model Card for Model ID
|
| 14 |
+
|
| 15 |
+
<!-- Provide a quick summary of what the model is/does. -->
|
| 16 |
+
|
| 17 |
+
|
| 18 |
+
|
| 19 |
+
## Model Details
|
| 20 |
+
|
| 21 |
+
### Model Description
|
| 22 |
+
|
| 23 |
+
<!-- Provide a longer summary of what this model is. -->
|
| 24 |
+
|
| 25 |
+
|
| 26 |
+
|
| 27 |
+
- **Developed by:** [More Information Needed]
|
| 28 |
+
- **Funded by [optional]:** [More Information Needed]
|
| 29 |
+
- **Shared by [optional]:** [More Information Needed]
|
| 30 |
+
- **Model type:** [More Information Needed]
|
| 31 |
+
- **Language(s) (NLP):** [More Information Needed]
|
| 32 |
+
- **License:** [More Information Needed]
|
| 33 |
+
- **Finetuned from model [optional]:** [More Information Needed]
|
| 34 |
+
|
| 35 |
+
### Model Sources [optional]
|
| 36 |
+
|
| 37 |
+
<!-- Provide the basic links for the model. -->
|
| 38 |
+
|
| 39 |
+
- **Repository:** [More Information Needed]
|
| 40 |
+
- **Paper [optional]:** [More Information Needed]
|
| 41 |
+
- **Demo [optional]:** [More Information Needed]
|
| 42 |
+
|
| 43 |
+
## Uses
|
| 44 |
+
|
| 45 |
+
<!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
|
| 46 |
+
|
| 47 |
+
### Direct Use
|
| 48 |
+
|
| 49 |
+
<!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
|
| 50 |
+
|
| 51 |
+
[More Information Needed]
|
| 52 |
+
|
| 53 |
+
### Downstream Use [optional]
|
| 54 |
+
|
| 55 |
+
<!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
|
| 56 |
+
|
| 57 |
+
[More Information Needed]
|
| 58 |
+
|
| 59 |
+
### Out-of-Scope Use
|
| 60 |
+
|
| 61 |
+
<!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
|
| 62 |
+
|
| 63 |
+
[More Information Needed]
|
| 64 |
+
|
| 65 |
+
## Bias, Risks, and Limitations
|
| 66 |
+
|
| 67 |
+
<!-- This section is meant to convey both technical and sociotechnical limitations. -->
|
| 68 |
+
|
| 69 |
+
[More Information Needed]
|
| 70 |
+
|
| 71 |
+
### Recommendations
|
| 72 |
+
|
| 73 |
+
<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
|
| 74 |
+
|
| 75 |
+
Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
|
| 76 |
+
|
| 77 |
+
## How to Get Started with the Model
|
| 78 |
+
|
| 79 |
+
Use the code below to get started with the model.
|
| 80 |
+
|
| 81 |
+
[More Information Needed]
|
| 82 |
+
|
| 83 |
+
## Training Details
|
| 84 |
+
|
| 85 |
+
### Training Data
|
| 86 |
+
|
| 87 |
+
<!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
|
| 88 |
+
|
| 89 |
+
[More Information Needed]
|
| 90 |
+
|
| 91 |
+
### Training Procedure
|
| 92 |
+
|
| 93 |
+
<!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
|
| 94 |
+
|
| 95 |
+
#### Preprocessing [optional]
|
| 96 |
+
|
| 97 |
+
[More Information Needed]
|
| 98 |
+
|
| 99 |
+
|
| 100 |
+
#### Training Hyperparameters
|
| 101 |
+
|
| 102 |
+
- **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
|
| 103 |
+
|
| 104 |
+
#### Speeds, Sizes, Times [optional]
|
| 105 |
+
|
| 106 |
+
<!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
|
| 107 |
+
|
| 108 |
+
[More Information Needed]
|
| 109 |
+
|
| 110 |
+
## Evaluation
|
| 111 |
+
|
| 112 |
+
<!-- This section describes the evaluation protocols and provides the results. -->
|
| 113 |
+
|
| 114 |
+
### Testing Data, Factors & Metrics
|
| 115 |
+
|
| 116 |
+
#### Testing Data
|
| 117 |
+
|
| 118 |
+
<!-- This should link to a Dataset Card if possible. -->
|
| 119 |
+
|
| 120 |
+
[More Information Needed]
|
| 121 |
+
|
| 122 |
+
#### Factors
|
| 123 |
+
|
| 124 |
+
<!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
|
| 125 |
+
|
| 126 |
+
[More Information Needed]
|
| 127 |
+
|
| 128 |
+
#### Metrics
|
| 129 |
+
|
| 130 |
+
<!-- These are the evaluation metrics being used, ideally with a description of why. -->
|
| 131 |
+
|
| 132 |
+
[More Information Needed]
|
| 133 |
+
|
| 134 |
+
### Results
|
| 135 |
+
|
| 136 |
+
[More Information Needed]
|
| 137 |
+
|
| 138 |
+
#### Summary
|
| 139 |
+
|
| 140 |
+
|
| 141 |
+
|
| 142 |
+
## Model Examination [optional]
|
| 143 |
+
|
| 144 |
+
<!-- Relevant interpretability work for the model goes here -->
|
| 145 |
+
|
| 146 |
+
[More Information Needed]
|
| 147 |
+
|
| 148 |
+
## Environmental Impact
|
| 149 |
+
|
| 150 |
+
<!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
|
| 151 |
+
|
| 152 |
+
Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
|
| 153 |
+
|
| 154 |
+
- **Hardware Type:** [More Information Needed]
|
| 155 |
+
- **Hours used:** [More Information Needed]
|
| 156 |
+
- **Cloud Provider:** [More Information Needed]
|
| 157 |
+
- **Compute Region:** [More Information Needed]
|
| 158 |
+
- **Carbon Emitted:** [More Information Needed]
|
| 159 |
+
|
| 160 |
+
## Technical Specifications [optional]
|
| 161 |
+
|
| 162 |
+
### Model Architecture and Objective
|
| 163 |
+
|
| 164 |
+
[More Information Needed]
|
| 165 |
+
|
| 166 |
+
### Compute Infrastructure
|
| 167 |
+
|
| 168 |
+
[More Information Needed]
|
| 169 |
+
|
| 170 |
+
#### Hardware
|
| 171 |
+
|
| 172 |
+
[More Information Needed]
|
| 173 |
+
|
| 174 |
+
#### Software
|
| 175 |
+
|
| 176 |
+
[More Information Needed]
|
| 177 |
+
|
| 178 |
+
## Citation [optional]
|
| 179 |
+
|
| 180 |
+
<!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
|
| 181 |
+
|
| 182 |
+
**BibTeX:**
|
| 183 |
+
|
| 184 |
+
[More Information Needed]
|
| 185 |
+
|
| 186 |
+
**APA:**
|
| 187 |
+
|
| 188 |
+
[More Information Needed]
|
| 189 |
+
|
| 190 |
+
## Glossary [optional]
|
| 191 |
+
|
| 192 |
+
<!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
|
| 193 |
+
|
| 194 |
+
[More Information Needed]
|
| 195 |
+
|
| 196 |
+
## More Information [optional]
|
| 197 |
+
|
| 198 |
+
[More Information Needed]
|
| 199 |
+
|
| 200 |
+
## Model Card Authors [optional]
|
| 201 |
+
|
| 202 |
+
[More Information Needed]
|
| 203 |
+
|
| 204 |
+
## Model Card Contact
|
| 205 |
+
|
| 206 |
+
[More Information Needed]
|
| 207 |
+
### Framework versions
|
| 208 |
+
|
| 209 |
+
- PEFT 0.18.1
|
overgeneralisation_original_Swedish/Qwen3.5-4B-Base_overgeneralisation_splits_original_features_train_overgeneralisation_splits_original_features_test1/checkpoint-1000/adapter_config.json
ADDED
|
@@ -0,0 +1,46 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
{
|
| 2 |
+
"alora_invocation_tokens": null,
|
| 3 |
+
"alpha_pattern": {},
|
| 4 |
+
"arrow_config": null,
|
| 5 |
+
"auto_mapping": null,
|
| 6 |
+
"base_model_name_or_path": "Qwen/Qwen3.5-4B-Base",
|
| 7 |
+
"bias": "none",
|
| 8 |
+
"corda_config": null,
|
| 9 |
+
"ensure_weight_tying": false,
|
| 10 |
+
"eva_config": null,
|
| 11 |
+
"exclude_modules": null,
|
| 12 |
+
"fan_in_fan_out": false,
|
| 13 |
+
"inference_mode": true,
|
| 14 |
+
"init_lora_weights": true,
|
| 15 |
+
"layer_replication": null,
|
| 16 |
+
"layers_pattern": null,
|
| 17 |
+
"layers_to_transform": null,
|
| 18 |
+
"loftq_config": {},
|
| 19 |
+
"lora_alpha": 256,
|
| 20 |
+
"lora_bias": false,
|
| 21 |
+
"lora_dropout": 0.0005183818805460705,
|
| 22 |
+
"megatron_config": null,
|
| 23 |
+
"megatron_core": "megatron.core",
|
| 24 |
+
"modules_to_save": null,
|
| 25 |
+
"peft_type": "LORA",
|
| 26 |
+
"peft_version": "0.18.1",
|
| 27 |
+
"qalora_group_size": 16,
|
| 28 |
+
"r": 128,
|
| 29 |
+
"rank_pattern": {},
|
| 30 |
+
"revision": null,
|
| 31 |
+
"target_modules": [
|
| 32 |
+
"up_proj",
|
| 33 |
+
"q_proj",
|
| 34 |
+
"o_proj",
|
| 35 |
+
"v_proj",
|
| 36 |
+
"k_proj",
|
| 37 |
+
"gate_proj",
|
| 38 |
+
"down_proj"
|
| 39 |
+
],
|
| 40 |
+
"target_parameters": null,
|
| 41 |
+
"task_type": "CAUSAL_LM",
|
| 42 |
+
"trainable_token_indices": null,
|
| 43 |
+
"use_dora": false,
|
| 44 |
+
"use_qalora": false,
|
| 45 |
+
"use_rslora": false
|
| 46 |
+
}
|
overgeneralisation_original_Swedish/Qwen3.5-4B-Base_overgeneralisation_splits_original_features_train_overgeneralisation_splits_original_features_test1/checkpoint-1000/chat_template.jinja
ADDED
|
@@ -0,0 +1,154 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
{%- set image_count = namespace(value=0) %}
|
| 2 |
+
{%- set video_count = namespace(value=0) %}
|
| 3 |
+
{%- macro render_content(content, do_vision_count, is_system_content=false) %}
|
| 4 |
+
{%- if content is string %}
|
| 5 |
+
{{- content }}
|
| 6 |
+
{%- elif content is iterable and content is not mapping %}
|
| 7 |
+
{%- for item in content %}
|
| 8 |
+
{%- if 'image' in item or 'image_url' in item or item.type == 'image' %}
|
| 9 |
+
{%- if is_system_content %}
|
| 10 |
+
{{- raise_exception('System message cannot contain images.') }}
|
| 11 |
+
{%- endif %}
|
| 12 |
+
{%- if do_vision_count %}
|
| 13 |
+
{%- set image_count.value = image_count.value + 1 %}
|
| 14 |
+
{%- endif %}
|
| 15 |
+
{%- if add_vision_id %}
|
| 16 |
+
{{- 'Picture ' ~ image_count.value ~ ': ' }}
|
| 17 |
+
{%- endif %}
|
| 18 |
+
{{- '<|vision_start|><|image_pad|><|vision_end|>' }}
|
| 19 |
+
{%- elif 'video' in item or item.type == 'video' %}
|
| 20 |
+
{%- if is_system_content %}
|
| 21 |
+
{{- raise_exception('System message cannot contain videos.') }}
|
| 22 |
+
{%- endif %}
|
| 23 |
+
{%- if do_vision_count %}
|
| 24 |
+
{%- set video_count.value = video_count.value + 1 %}
|
| 25 |
+
{%- endif %}
|
| 26 |
+
{%- if add_vision_id %}
|
| 27 |
+
{{- 'Video ' ~ video_count.value ~ ': ' }}
|
| 28 |
+
{%- endif %}
|
| 29 |
+
{{- '<|vision_start|><|video_pad|><|vision_end|>' }}
|
| 30 |
+
{%- elif 'text' in item %}
|
| 31 |
+
{{- item.text }}
|
| 32 |
+
{%- else %}
|
| 33 |
+
{{- raise_exception('Unexpected item type in content.') }}
|
| 34 |
+
{%- endif %}
|
| 35 |
+
{%- endfor %}
|
| 36 |
+
{%- elif content is none or content is undefined %}
|
| 37 |
+
{{- '' }}
|
| 38 |
+
{%- else %}
|
| 39 |
+
{{- raise_exception('Unexpected content type.') }}
|
| 40 |
+
{%- endif %}
|
| 41 |
+
{%- endmacro %}
|
| 42 |
+
{%- if not messages %}
|
| 43 |
+
{{- raise_exception('No messages provided.') }}
|
| 44 |
+
{%- endif %}
|
| 45 |
+
{%- if tools and tools is iterable and tools is not mapping %}
|
| 46 |
+
{{- '<|im_start|>system\n' }}
|
| 47 |
+
{{- "# Tools\n\nYou have access to the following functions:\n\n<tools>" }}
|
| 48 |
+
{%- for tool in tools %}
|
| 49 |
+
{{- "\n" }}
|
| 50 |
+
{{- tool | tojson }}
|
| 51 |
+
{%- endfor %}
|
| 52 |
+
{{- "\n</tools>" }}
|
| 53 |
+
{{- '\n\nIf you choose to call a function ONLY reply in the following format with NO suffix:\n\n<tool_call>\n<function=example_function_name>\n<parameter=example_parameter_1>\nvalue_1\n</parameter>\n<parameter=example_parameter_2>\nThis is the value for the second parameter\nthat can span\nmultiple lines\n</parameter>\n</function>\n</tool_call>\n\n<IMPORTANT>\nReminder:\n- Function calls MUST follow the specified format: an inner <function=...></function> block must be nested within <tool_call></tool_call> XML tags\n- Required parameters MUST be specified\n- You may provide optional reasoning for your function call in natural language BEFORE the function call, but NOT after\n- If there is no function call available, answer the question like normal with your current knowledge and do not tell the user about function calls\n</IMPORTANT>' }}
|
| 54 |
+
{%- if messages[0].role == 'system' %}
|
| 55 |
+
{%- set content = render_content(messages[0].content, false, true)|trim %}
|
| 56 |
+
{%- if content %}
|
| 57 |
+
{{- '\n\n' + content }}
|
| 58 |
+
{%- endif %}
|
| 59 |
+
{%- endif %}
|
| 60 |
+
{{- '<|im_end|>\n' }}
|
| 61 |
+
{%- else %}
|
| 62 |
+
{%- if messages[0].role == 'system' %}
|
| 63 |
+
{%- set content = render_content(messages[0].content, false, true)|trim %}
|
| 64 |
+
{{- '<|im_start|>system\n' + content + '<|im_end|>\n' }}
|
| 65 |
+
{%- endif %}
|
| 66 |
+
{%- endif %}
|
| 67 |
+
{%- set ns = namespace(multi_step_tool=true, last_query_index=messages|length - 1) %}
|
| 68 |
+
{%- for message in messages[::-1] %}
|
| 69 |
+
{%- set index = (messages|length - 1) - loop.index0 %}
|
| 70 |
+
{%- if ns.multi_step_tool and message.role == "user" %}
|
| 71 |
+
{%- set content = render_content(message.content, false)|trim %}
|
| 72 |
+
{%- if not(content.startswith('<tool_response>') and content.endswith('</tool_response>')) %}
|
| 73 |
+
{%- set ns.multi_step_tool = false %}
|
| 74 |
+
{%- set ns.last_query_index = index %}
|
| 75 |
+
{%- endif %}
|
| 76 |
+
{%- endif %}
|
| 77 |
+
{%- endfor %}
|
| 78 |
+
{%- if ns.multi_step_tool %}
|
| 79 |
+
{{- raise_exception('No user query found in messages.') }}
|
| 80 |
+
{%- endif %}
|
| 81 |
+
{%- for message in messages %}
|
| 82 |
+
{%- set content = render_content(message.content, true)|trim %}
|
| 83 |
+
{%- if message.role == "system" %}
|
| 84 |
+
{%- if not loop.first %}
|
| 85 |
+
{{- raise_exception('System message must be at the beginning.') }}
|
| 86 |
+
{%- endif %}
|
| 87 |
+
{%- elif message.role == "user" %}
|
| 88 |
+
{{- '<|im_start|>' + message.role + '\n' + content + '<|im_end|>' + '\n' }}
|
| 89 |
+
{%- elif message.role == "assistant" %}
|
| 90 |
+
{%- set reasoning_content = '' %}
|
| 91 |
+
{%- if message.reasoning_content is string %}
|
| 92 |
+
{%- set reasoning_content = message.reasoning_content %}
|
| 93 |
+
{%- else %}
|
| 94 |
+
{%- if '</think>' in content %}
|
| 95 |
+
{%- set reasoning_content = content.split('</think>')[0].rstrip('\n').split('<think>')[-1].lstrip('\n') %}
|
| 96 |
+
{%- set content = content.split('</think>')[-1].lstrip('\n') %}
|
| 97 |
+
{%- endif %}
|
| 98 |
+
{%- endif %}
|
| 99 |
+
{%- set reasoning_content = reasoning_content|trim %}
|
| 100 |
+
{%- if loop.index0 > ns.last_query_index %}
|
| 101 |
+
{{- '<|im_start|>' + message.role + '\n<think>\n' + reasoning_content + '\n</think>\n\n' + content }}
|
| 102 |
+
{%- else %}
|
| 103 |
+
{{- '<|im_start|>' + message.role + '\n' + content }}
|
| 104 |
+
{%- endif %}
|
| 105 |
+
{%- if message.tool_calls and message.tool_calls is iterable and message.tool_calls is not mapping %}
|
| 106 |
+
{%- for tool_call in message.tool_calls %}
|
| 107 |
+
{%- if tool_call.function is defined %}
|
| 108 |
+
{%- set tool_call = tool_call.function %}
|
| 109 |
+
{%- endif %}
|
| 110 |
+
{%- if loop.first %}
|
| 111 |
+
{%- if content|trim %}
|
| 112 |
+
{{- '\n\n<tool_call>\n<function=' + tool_call.name + '>\n' }}
|
| 113 |
+
{%- else %}
|
| 114 |
+
{{- '<tool_call>\n<function=' + tool_call.name + '>\n' }}
|
| 115 |
+
{%- endif %}
|
| 116 |
+
{%- else %}
|
| 117 |
+
{{- '\n<tool_call>\n<function=' + tool_call.name + '>\n' }}
|
| 118 |
+
{%- endif %}
|
| 119 |
+
{%- if tool_call.arguments is defined %}
|
| 120 |
+
{%- for args_name, args_value in tool_call.arguments|items %}
|
| 121 |
+
{{- '<parameter=' + args_name + '>\n' }}
|
| 122 |
+
{%- set args_value = args_value | tojson | safe if args_value is mapping or (args_value is sequence and args_value is not string) else args_value | string %}
|
| 123 |
+
{{- args_value }}
|
| 124 |
+
{{- '\n</parameter>\n' }}
|
| 125 |
+
{%- endfor %}
|
| 126 |
+
{%- endif %}
|
| 127 |
+
{{- '</function>\n</tool_call>' }}
|
| 128 |
+
{%- endfor %}
|
| 129 |
+
{%- endif %}
|
| 130 |
+
{{- '<|im_end|>\n' }}
|
| 131 |
+
{%- elif message.role == "tool" %}
|
| 132 |
+
{%- if loop.previtem and loop.previtem.role != "tool" %}
|
| 133 |
+
{{- '<|im_start|>user' }}
|
| 134 |
+
{%- endif %}
|
| 135 |
+
{{- '\n<tool_response>\n' }}
|
| 136 |
+
{{- content }}
|
| 137 |
+
{{- '\n</tool_response>' }}
|
| 138 |
+
{%- if not loop.last and loop.nextitem.role != "tool" %}
|
| 139 |
+
{{- '<|im_end|>\n' }}
|
| 140 |
+
{%- elif loop.last %}
|
| 141 |
+
{{- '<|im_end|>\n' }}
|
| 142 |
+
{%- endif %}
|
| 143 |
+
{%- else %}
|
| 144 |
+
{{- raise_exception('Unexpected message role.') }}
|
| 145 |
+
{%- endif %}
|
| 146 |
+
{%- endfor %}
|
| 147 |
+
{%- if add_generation_prompt %}
|
| 148 |
+
{{- '<|im_start|>assistant\n' }}
|
| 149 |
+
{%- if enable_thinking is defined and enable_thinking is false %}
|
| 150 |
+
{{- '<think>\n\n</think>\n\n' }}
|
| 151 |
+
{%- else %}
|
| 152 |
+
{{- '<think>\n' }}
|
| 153 |
+
{%- endif %}
|
| 154 |
+
{%- endif %}
|
overgeneralisation_original_Swedish/Qwen3.5-4B-Base_overgeneralisation_splits_original_features_train_overgeneralisation_splits_original_features_test1/checkpoint-1000/tokenizer_config.json
ADDED
|
@@ -0,0 +1,31 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
{
|
| 2 |
+
"add_prefix_space": false,
|
| 3 |
+
"audio_bos_token": "<|audio_start|>",
|
| 4 |
+
"audio_eos_token": "<|audio_end|>",
|
| 5 |
+
"audio_token": "<|audio_pad|>",
|
| 6 |
+
"backend": "tokenizers",
|
| 7 |
+
"bos_token": null,
|
| 8 |
+
"clean_up_tokenization_spaces": false,
|
| 9 |
+
"eos_token": "<|endoftext|>",
|
| 10 |
+
"errors": "replace",
|
| 11 |
+
"image_token": "<|image_pad|>",
|
| 12 |
+
"is_local": false,
|
| 13 |
+
"model_max_length": 262144,
|
| 14 |
+
"model_specific_special_tokens": {
|
| 15 |
+
"audio_bos_token": "<|audio_start|>",
|
| 16 |
+
"audio_eos_token": "<|audio_end|>",
|
| 17 |
+
"audio_token": "<|audio_pad|>",
|
| 18 |
+
"image_token": "<|image_pad|>",
|
| 19 |
+
"video_token": "<|video_pad|>",
|
| 20 |
+
"vision_bos_token": "<|vision_start|>",
|
| 21 |
+
"vision_eos_token": "<|vision_end|>"
|
| 22 |
+
},
|
| 23 |
+
"pad_token": "<|endoftext|>",
|
| 24 |
+
"pretokenize_regex": "(?i:'s|'t|'re|'ve|'m|'ll|'d)|[^\\r\\n\\p{L}\\p{N}]?[\\p{L}\\p{M}]+|\\p{N}| ?[^\\s\\p{L}\\p{M}\\p{N}]+[\\r\\n]*|\\s*[\\r\\n]+|\\s+(?!\\S)|\\s+",
|
| 25 |
+
"split_special_tokens": false,
|
| 26 |
+
"tokenizer_class": "TokenizersBackend",
|
| 27 |
+
"unk_token": null,
|
| 28 |
+
"video_token": "<|video_pad|>",
|
| 29 |
+
"vision_bos_token": "<|vision_start|>",
|
| 30 |
+
"vision_eos_token": "<|vision_end|>"
|
| 31 |
+
}
|
overgeneralisation_original_Swedish/Qwen3.5-4B-Base_overgeneralisation_splits_original_features_train_overgeneralisation_splits_original_features_test1/checkpoint-1000/trainer_state.json
ADDED
|
@@ -0,0 +1,1084 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
{
|
| 2 |
+
"best_global_step": null,
|
| 3 |
+
"best_metric": null,
|
| 4 |
+
"best_model_checkpoint": null,
|
| 5 |
+
"epoch": 2.488169364881694,
|
| 6 |
+
"eval_steps": 20,
|
| 7 |
+
"global_step": 1000,
|
| 8 |
+
"is_hyper_param_search": false,
|
| 9 |
+
"is_local_process_zero": true,
|
| 10 |
+
"is_world_process_zero": true,
|
| 11 |
+
"log_history": [
|
| 12 |
+
{
|
| 13 |
+
"entropy": 1.9784346982836722,
|
| 14 |
+
"epoch": 0.049813200498132,
|
| 15 |
+
"grad_norm": 3.0229668617248535,
|
| 16 |
+
"learning_rate": 9.526142962415369e-06,
|
| 17 |
+
"loss": 1.7360023498535155,
|
| 18 |
+
"mean_token_accuracy": 0.6449888605624438,
|
| 19 |
+
"num_tokens": 46794.0,
|
| 20 |
+
"step": 20
|
| 21 |
+
},
|
| 22 |
+
{
|
| 23 |
+
"epoch": 0.049813200498132,
|
| 24 |
+
"eval_entropy": 1.41506897571475,
|
| 25 |
+
"eval_loss": 1.1876318454742432,
|
| 26 |
+
"eval_mean_token_accuracy": 0.734131895525511,
|
| 27 |
+
"eval_num_tokens": 46794.0,
|
| 28 |
+
"eval_runtime": 87.8071,
|
| 29 |
+
"eval_samples_per_second": 15.671,
|
| 30 |
+
"eval_steps_per_second": 1.959,
|
| 31 |
+
"step": 20
|
| 32 |
+
},
|
| 33 |
+
{
|
| 34 |
+
"entropy": 1.049924298375845,
|
| 35 |
+
"epoch": 0.099626400996264,
|
| 36 |
+
"grad_norm": 1.5795097351074219,
|
| 37 |
+
"learning_rate": 1.9553661870221022e-05,
|
| 38 |
+
"loss": 0.8944448471069336,
|
| 39 |
+
"mean_token_accuracy": 0.7748479396104813,
|
| 40 |
+
"num_tokens": 90754.0,
|
| 41 |
+
"step": 40
|
| 42 |
+
},
|
| 43 |
+
{
|
| 44 |
+
"epoch": 0.099626400996264,
|
| 45 |
+
"eval_entropy": 0.7996658658565476,
|
| 46 |
+
"eval_loss": 0.7202735543251038,
|
| 47 |
+
"eval_mean_token_accuracy": 0.8070558306089667,
|
| 48 |
+
"eval_num_tokens": 90754.0,
|
| 49 |
+
"eval_runtime": 86.9199,
|
| 50 |
+
"eval_samples_per_second": 15.831,
|
| 51 |
+
"eval_steps_per_second": 1.979,
|
| 52 |
+
"step": 40
|
| 53 |
+
},
|
| 54 |
+
{
|
| 55 |
+
"entropy": 0.7734908878803253,
|
| 56 |
+
"epoch": 0.149439601494396,
|
| 57 |
+
"grad_norm": 1.3136248588562012,
|
| 58 |
+
"learning_rate": 2.9581180778026673e-05,
|
| 59 |
+
"loss": 0.6780608654022217,
|
| 60 |
+
"mean_token_accuracy": 0.8168170280754566,
|
| 61 |
+
"num_tokens": 137472.0,
|
| 62 |
+
"step": 60
|
| 63 |
+
},
|
| 64 |
+
{
|
| 65 |
+
"epoch": 0.149439601494396,
|
| 66 |
+
"eval_entropy": 0.7119324009778888,
|
| 67 |
+
"eval_loss": 0.6554311513900757,
|
| 68 |
+
"eval_mean_token_accuracy": 0.8215604798738346,
|
| 69 |
+
"eval_num_tokens": 137472.0,
|
| 70 |
+
"eval_runtime": 86.8692,
|
| 71 |
+
"eval_samples_per_second": 15.84,
|
| 72 |
+
"eval_steps_per_second": 1.98,
|
| 73 |
+
"step": 60
|
| 74 |
+
},
|
| 75 |
+
{
|
| 76 |
+
"entropy": 0.7071127541363239,
|
| 77 |
+
"epoch": 0.199252801992528,
|
| 78 |
+
"grad_norm": 1.387060284614563,
|
| 79 |
+
"learning_rate": 3.960869968583232e-05,
|
| 80 |
+
"loss": 0.6382100582122803,
|
| 81 |
+
"mean_token_accuracy": 0.8229366384446621,
|
| 82 |
+
"num_tokens": 187408.0,
|
| 83 |
+
"step": 80
|
| 84 |
+
},
|
| 85 |
+
{
|
| 86 |
+
"epoch": 0.199252801992528,
|
| 87 |
+
"eval_entropy": 0.6883931482254073,
|
| 88 |
+
"eval_loss": 0.625065803527832,
|
| 89 |
+
"eval_mean_token_accuracy": 0.828940509710201,
|
| 90 |
+
"eval_num_tokens": 187408.0,
|
| 91 |
+
"eval_runtime": 86.662,
|
| 92 |
+
"eval_samples_per_second": 15.878,
|
| 93 |
+
"eval_steps_per_second": 1.985,
|
| 94 |
+
"step": 80
|
| 95 |
+
},
|
| 96 |
+
{
|
| 97 |
+
"entropy": 0.6800824083387852,
|
| 98 |
+
"epoch": 0.24906600249066002,
|
| 99 |
+
"grad_norm": 0.9892916679382324,
|
| 100 |
+
"learning_rate": 4.963621859363797e-05,
|
| 101 |
+
"loss": 0.6011715888977051,
|
| 102 |
+
"mean_token_accuracy": 0.8323964163661003,
|
| 103 |
+
"num_tokens": 234197.0,
|
| 104 |
+
"step": 100
|
| 105 |
+
},
|
| 106 |
+
{
|
| 107 |
+
"epoch": 0.24906600249066002,
|
| 108 |
+
"eval_entropy": 0.6840810470802839,
|
| 109 |
+
"eval_loss": 0.6037028431892395,
|
| 110 |
+
"eval_mean_token_accuracy": 0.8309669033732525,
|
| 111 |
+
"eval_num_tokens": 234197.0,
|
| 112 |
+
"eval_runtime": 86.4637,
|
| 113 |
+
"eval_samples_per_second": 15.914,
|
| 114 |
+
"eval_steps_per_second": 1.989,
|
| 115 |
+
"step": 100
|
| 116 |
+
},
|
| 117 |
+
{
|
| 118 |
+
"entropy": 0.6776216626167297,
|
| 119 |
+
"epoch": 0.298879202988792,
|
| 120 |
+
"grad_norm": 0.8918434977531433,
|
| 121 |
+
"learning_rate": 5.9663737501443624e-05,
|
| 122 |
+
"loss": 0.5991742610931396,
|
| 123 |
+
"mean_token_accuracy": 0.8300838828086853,
|
| 124 |
+
"num_tokens": 281241.0,
|
| 125 |
+
"step": 120
|
| 126 |
+
},
|
| 127 |
+
{
|
| 128 |
+
"epoch": 0.298879202988792,
|
| 129 |
+
"eval_entropy": 0.690427724705186,
|
| 130 |
+
"eval_loss": 0.5939701795578003,
|
| 131 |
+
"eval_mean_token_accuracy": 0.8345950186945671,
|
| 132 |
+
"eval_num_tokens": 281241.0,
|
| 133 |
+
"eval_runtime": 86.6626,
|
| 134 |
+
"eval_samples_per_second": 15.878,
|
| 135 |
+
"eval_steps_per_second": 1.985,
|
| 136 |
+
"step": 120
|
| 137 |
+
},
|
| 138 |
+
{
|
| 139 |
+
"entropy": 0.6709842771291733,
|
| 140 |
+
"epoch": 0.34869240348692404,
|
| 141 |
+
"grad_norm": 0.9135531187057495,
|
| 142 |
+
"learning_rate": 6.969125640924927e-05,
|
| 143 |
+
"loss": 0.5914147377014161,
|
| 144 |
+
"mean_token_accuracy": 0.8314545609056949,
|
| 145 |
+
"num_tokens": 327393.0,
|
| 146 |
+
"step": 140
|
| 147 |
+
},
|
| 148 |
+
{
|
| 149 |
+
"epoch": 0.34869240348692404,
|
| 150 |
+
"eval_entropy": 0.6584504666023476,
|
| 151 |
+
"eval_loss": 0.5849721431732178,
|
| 152 |
+
"eval_mean_token_accuracy": 0.8357757236375365,
|
| 153 |
+
"eval_num_tokens": 327393.0,
|
| 154 |
+
"eval_runtime": 86.3262,
|
| 155 |
+
"eval_samples_per_second": 15.94,
|
| 156 |
+
"eval_steps_per_second": 1.992,
|
| 157 |
+
"step": 140
|
| 158 |
+
},
|
| 159 |
+
{
|
| 160 |
+
"entropy": 0.6524647936224938,
|
| 161 |
+
"epoch": 0.398505603985056,
|
| 162 |
+
"grad_norm": 0.8651587963104248,
|
| 163 |
+
"learning_rate": 7.971877531705493e-05,
|
| 164 |
+
"loss": 0.5710843563079834,
|
| 165 |
+
"mean_token_accuracy": 0.8396127380430698,
|
| 166 |
+
"num_tokens": 373834.0,
|
| 167 |
+
"step": 160
|
| 168 |
+
},
|
| 169 |
+
{
|
| 170 |
+
"epoch": 0.398505603985056,
|
| 171 |
+
"eval_entropy": 0.6283470298661742,
|
| 172 |
+
"eval_loss": 0.5738973617553711,
|
| 173 |
+
"eval_mean_token_accuracy": 0.8379981181649274,
|
| 174 |
+
"eval_num_tokens": 373834.0,
|
| 175 |
+
"eval_runtime": 86.5619,
|
| 176 |
+
"eval_samples_per_second": 15.896,
|
| 177 |
+
"eval_steps_per_second": 1.987,
|
| 178 |
+
"step": 160
|
| 179 |
+
},
|
| 180 |
+
{
|
| 181 |
+
"entropy": 0.6450445972383022,
|
| 182 |
+
"epoch": 0.44831880448318806,
|
| 183 |
+
"grad_norm": 0.8661723732948303,
|
| 184 |
+
"learning_rate": 8.974629422486058e-05,
|
| 185 |
+
"loss": 0.5677794933319091,
|
| 186 |
+
"mean_token_accuracy": 0.8389350369572639,
|
| 187 |
+
"num_tokens": 422572.0,
|
| 188 |
+
"step": 180
|
| 189 |
+
},
|
| 190 |
+
{
|
| 191 |
+
"epoch": 0.44831880448318806,
|
| 192 |
+
"eval_entropy": 0.6142613257086554,
|
| 193 |
+
"eval_loss": 0.5698265433311462,
|
| 194 |
+
"eval_mean_token_accuracy": 0.8388577273418737,
|
| 195 |
+
"eval_num_tokens": 422572.0,
|
| 196 |
+
"eval_runtime": 86.4443,
|
| 197 |
+
"eval_samples_per_second": 15.918,
|
| 198 |
+
"eval_steps_per_second": 1.99,
|
| 199 |
+
"step": 180
|
| 200 |
+
},
|
| 201 |
+
{
|
| 202 |
+
"entropy": 0.6448334597051144,
|
| 203 |
+
"epoch": 0.49813200498132004,
|
| 204 |
+
"grad_norm": 0.9662242531776428,
|
| 205 |
+
"learning_rate": 9.977381313266624e-05,
|
| 206 |
+
"loss": 0.581433916091919,
|
| 207 |
+
"mean_token_accuracy": 0.8387043006718159,
|
| 208 |
+
"num_tokens": 471879.0,
|
| 209 |
+
"step": 200
|
| 210 |
+
},
|
| 211 |
+
{
|
| 212 |
+
"epoch": 0.49813200498132004,
|
| 213 |
+
"eval_entropy": 0.6154296522916749,
|
| 214 |
+
"eval_loss": 0.5660303831100464,
|
| 215 |
+
"eval_mean_token_accuracy": 0.8412494766850804,
|
| 216 |
+
"eval_num_tokens": 471879.0,
|
| 217 |
+
"eval_runtime": 86.3063,
|
| 218 |
+
"eval_samples_per_second": 15.943,
|
| 219 |
+
"eval_steps_per_second": 1.993,
|
| 220 |
+
"step": 200
|
| 221 |
+
},
|
| 222 |
+
{
|
| 223 |
+
"entropy": 0.6376728117465973,
|
| 224 |
+
"epoch": 0.547945205479452,
|
| 225 |
+
"grad_norm": 0.7618638873100281,
|
| 226 |
+
"learning_rate": 0.00010980133204047189,
|
| 227 |
+
"loss": 0.5678351402282715,
|
| 228 |
+
"mean_token_accuracy": 0.8404546812176704,
|
| 229 |
+
"num_tokens": 520984.0,
|
| 230 |
+
"step": 220
|
| 231 |
+
},
|
| 232 |
+
{
|
| 233 |
+
"epoch": 0.547945205479452,
|
| 234 |
+
"eval_entropy": 0.6181817033956217,
|
| 235 |
+
"eval_loss": 0.5663750171661377,
|
| 236 |
+
"eval_mean_token_accuracy": 0.8388350962899452,
|
| 237 |
+
"eval_num_tokens": 520984.0,
|
| 238 |
+
"eval_runtime": 86.5904,
|
| 239 |
+
"eval_samples_per_second": 15.891,
|
| 240 |
+
"eval_steps_per_second": 1.986,
|
| 241 |
+
"step": 220
|
| 242 |
+
},
|
| 243 |
+
{
|
| 244 |
+
"entropy": 0.6303176879882812,
|
| 245 |
+
"epoch": 0.597758405977584,
|
| 246 |
+
"grad_norm": 0.7571695446968079,
|
| 247 |
+
"learning_rate": 0.00011982885094827753,
|
| 248 |
+
"loss": 0.5502778053283691,
|
| 249 |
+
"mean_token_accuracy": 0.8429657347500324,
|
| 250 |
+
"num_tokens": 566596.0,
|
| 251 |
+
"step": 240
|
| 252 |
+
},
|
| 253 |
+
{
|
| 254 |
+
"epoch": 0.597758405977584,
|
| 255 |
+
"eval_entropy": 0.6252533817707107,
|
| 256 |
+
"eval_loss": 0.5570284128189087,
|
| 257 |
+
"eval_mean_token_accuracy": 0.8427327847064927,
|
| 258 |
+
"eval_num_tokens": 566596.0,
|
| 259 |
+
"eval_runtime": 86.4157,
|
| 260 |
+
"eval_samples_per_second": 15.923,
|
| 261 |
+
"eval_steps_per_second": 1.99,
|
| 262 |
+
"step": 240
|
| 263 |
+
},
|
| 264 |
+
{
|
| 265 |
+
"entropy": 0.6202544964849949,
|
| 266 |
+
"epoch": 0.6475716064757161,
|
| 267 |
+
"grad_norm": 0.6447190642356873,
|
| 268 |
+
"learning_rate": 0.00012985636985608318,
|
| 269 |
+
"loss": 0.5485352993011474,
|
| 270 |
+
"mean_token_accuracy": 0.844165726006031,
|
| 271 |
+
"num_tokens": 613603.0,
|
| 272 |
+
"step": 260
|
| 273 |
+
},
|
| 274 |
+
{
|
| 275 |
+
"epoch": 0.6475716064757161,
|
| 276 |
+
"eval_entropy": 0.6441633552312851,
|
| 277 |
+
"eval_loss": 0.5606644153594971,
|
| 278 |
+
"eval_mean_token_accuracy": 0.842403513054515,
|
| 279 |
+
"eval_num_tokens": 613603.0,
|
| 280 |
+
"eval_runtime": 86.6343,
|
| 281 |
+
"eval_samples_per_second": 15.883,
|
| 282 |
+
"eval_steps_per_second": 1.985,
|
| 283 |
+
"step": 260
|
| 284 |
+
},
|
| 285 |
+
{
|
| 286 |
+
"entropy": 0.6306711677461863,
|
| 287 |
+
"epoch": 0.6973848069738481,
|
| 288 |
+
"grad_norm": 0.7869907021522522,
|
| 289 |
+
"learning_rate": 0.00013988388876388883,
|
| 290 |
+
"loss": 0.5579307556152344,
|
| 291 |
+
"mean_token_accuracy": 0.841247134655714,
|
| 292 |
+
"num_tokens": 658565.0,
|
| 293 |
+
"step": 280
|
| 294 |
+
},
|
| 295 |
+
{
|
| 296 |
+
"epoch": 0.6973848069738481,
|
| 297 |
+
"eval_entropy": 0.6263934678809587,
|
| 298 |
+
"eval_loss": 0.5559113025665283,
|
| 299 |
+
"eval_mean_token_accuracy": 0.8427334743183713,
|
| 300 |
+
"eval_num_tokens": 658565.0,
|
| 301 |
+
"eval_runtime": 86.6403,
|
| 302 |
+
"eval_samples_per_second": 15.882,
|
| 303 |
+
"eval_steps_per_second": 1.985,
|
| 304 |
+
"step": 280
|
| 305 |
+
},
|
| 306 |
+
{
|
| 307 |
+
"entropy": 0.6385872110724449,
|
| 308 |
+
"epoch": 0.7471980074719801,
|
| 309 |
+
"grad_norm": 0.6679229736328125,
|
| 310 |
+
"learning_rate": 0.0001499114076716945,
|
| 311 |
+
"loss": 0.5667279720306396,
|
| 312 |
+
"mean_token_accuracy": 0.8389136254787445,
|
| 313 |
+
"num_tokens": 705680.0,
|
| 314 |
+
"step": 300
|
| 315 |
+
},
|
| 316 |
+
{
|
| 317 |
+
"epoch": 0.7471980074719801,
|
| 318 |
+
"eval_entropy": 0.6141417321077612,
|
| 319 |
+
"eval_loss": 0.5570600628852844,
|
| 320 |
+
"eval_mean_token_accuracy": 0.8437647996253745,
|
| 321 |
+
"eval_num_tokens": 705680.0,
|
| 322 |
+
"eval_runtime": 86.7588,
|
| 323 |
+
"eval_samples_per_second": 15.86,
|
| 324 |
+
"eval_steps_per_second": 1.983,
|
| 325 |
+
"step": 300
|
| 326 |
+
},
|
| 327 |
+
{
|
| 328 |
+
"entropy": 0.6199494235217571,
|
| 329 |
+
"epoch": 0.797011207970112,
|
| 330 |
+
"grad_norm": 0.7924400568008423,
|
| 331 |
+
"learning_rate": 0.00015993892657950015,
|
| 332 |
+
"loss": 0.5529299736022949,
|
| 333 |
+
"mean_token_accuracy": 0.8426973208785057,
|
| 334 |
+
"num_tokens": 752616.0,
|
| 335 |
+
"step": 320
|
| 336 |
+
},
|
| 337 |
+
{
|
| 338 |
+
"epoch": 0.797011207970112,
|
| 339 |
+
"eval_entropy": 0.6133768925833147,
|
| 340 |
+
"eval_loss": 0.556602418422699,
|
| 341 |
+
"eval_mean_token_accuracy": 0.8432947965555413,
|
| 342 |
+
"eval_num_tokens": 752616.0,
|
| 343 |
+
"eval_runtime": 86.492,
|
| 344 |
+
"eval_samples_per_second": 15.909,
|
| 345 |
+
"eval_steps_per_second": 1.989,
|
| 346 |
+
"step": 320
|
| 347 |
+
},
|
| 348 |
+
{
|
| 349 |
+
"entropy": 0.6203986253589392,
|
| 350 |
+
"epoch": 0.8468244084682441,
|
| 351 |
+
"grad_norm": 0.8364354372024536,
|
| 352 |
+
"learning_rate": 0.00016996644548730578,
|
| 353 |
+
"loss": 0.5551144123077393,
|
| 354 |
+
"mean_token_accuracy": 0.8432973213493824,
|
| 355 |
+
"num_tokens": 797151.0,
|
| 356 |
+
"step": 340
|
| 357 |
+
},
|
| 358 |
+
{
|
| 359 |
+
"epoch": 0.8468244084682441,
|
| 360 |
+
"eval_entropy": 0.6017442844634833,
|
| 361 |
+
"eval_loss": 0.5566568374633789,
|
| 362 |
+
"eval_mean_token_accuracy": 0.8437666123689607,
|
| 363 |
+
"eval_num_tokens": 797151.0,
|
| 364 |
+
"eval_runtime": 86.5552,
|
| 365 |
+
"eval_samples_per_second": 15.897,
|
| 366 |
+
"eval_steps_per_second": 1.987,
|
| 367 |
+
"step": 340
|
| 368 |
+
},
|
| 369 |
+
{
|
| 370 |
+
"entropy": 0.6341533534228802,
|
| 371 |
+
"epoch": 0.8966376089663761,
|
| 372 |
+
"grad_norm": 0.7783445715904236,
|
| 373 |
+
"learning_rate": 0.00017999396439511144,
|
| 374 |
+
"loss": 0.5669133186340332,
|
| 375 |
+
"mean_token_accuracy": 0.8379446342587471,
|
| 376 |
+
"num_tokens": 843585.0,
|
| 377 |
+
"step": 360
|
| 378 |
+
},
|
| 379 |
+
{
|
| 380 |
+
"epoch": 0.8966376089663761,
|
| 381 |
+
"eval_entropy": 0.6055107958788095,
|
| 382 |
+
"eval_loss": 0.5599350333213806,
|
| 383 |
+
"eval_mean_token_accuracy": 0.8435030894917112,
|
| 384 |
+
"eval_num_tokens": 843585.0,
|
| 385 |
+
"eval_runtime": 86.4814,
|
| 386 |
+
"eval_samples_per_second": 15.911,
|
| 387 |
+
"eval_steps_per_second": 1.989,
|
| 388 |
+
"step": 360
|
| 389 |
+
},
|
| 390 |
+
{
|
| 391 |
+
"entropy": 0.6306198488920927,
|
| 392 |
+
"epoch": 0.9464508094645081,
|
| 393 |
+
"grad_norm": 0.8449786901473999,
|
| 394 |
+
"learning_rate": 0.0001900214833029171,
|
| 395 |
+
"loss": 0.5739435195922852,
|
| 396 |
+
"mean_token_accuracy": 0.8393832489848136,
|
| 397 |
+
"num_tokens": 889842.0,
|
| 398 |
+
"step": 380
|
| 399 |
+
},
|
| 400 |
+
{
|
| 401 |
+
"epoch": 0.9464508094645081,
|
| 402 |
+
"eval_entropy": 0.6129532439071078,
|
| 403 |
+
"eval_loss": 0.5566295981407166,
|
| 404 |
+
"eval_mean_token_accuracy": 0.8430350880290187,
|
| 405 |
+
"eval_num_tokens": 889842.0,
|
| 406 |
+
"eval_runtime": 86.4643,
|
| 407 |
+
"eval_samples_per_second": 15.914,
|
| 408 |
+
"eval_steps_per_second": 1.989,
|
| 409 |
+
"step": 380
|
| 410 |
+
},
|
| 411 |
+
{
|
| 412 |
+
"entropy": 0.6203123550862074,
|
| 413 |
+
"epoch": 0.9962640099626401,
|
| 414 |
+
"grad_norm": 0.7334314584732056,
|
| 415 |
+
"learning_rate": 0.00020004900221072276,
|
| 416 |
+
"loss": 0.5547565937042236,
|
| 417 |
+
"mean_token_accuracy": 0.8403573960065842,
|
| 418 |
+
"num_tokens": 935589.0,
|
| 419 |
+
"step": 400
|
| 420 |
+
},
|
| 421 |
+
{
|
| 422 |
+
"epoch": 0.9962640099626401,
|
| 423 |
+
"eval_entropy": 0.6275761647279873,
|
| 424 |
+
"eval_loss": 0.5621116757392883,
|
| 425 |
+
"eval_mean_token_accuracy": 0.841587379228237,
|
| 426 |
+
"eval_num_tokens": 935589.0,
|
| 427 |
+
"eval_runtime": 86.4748,
|
| 428 |
+
"eval_samples_per_second": 15.912,
|
| 429 |
+
"eval_steps_per_second": 1.989,
|
| 430 |
+
"step": 400
|
| 431 |
+
},
|
| 432 |
+
{
|
| 433 |
+
"entropy": 0.5795013002860241,
|
| 434 |
+
"epoch": 1.0448318804483188,
|
| 435 |
+
"grad_norm": 0.8858296871185303,
|
| 436 |
+
"learning_rate": 0.0002015421505577756,
|
| 437 |
+
"loss": 0.5183939933776855,
|
| 438 |
+
"mean_token_accuracy": 0.850081592034071,
|
| 439 |
+
"num_tokens": 980589.0,
|
| 440 |
+
"step": 420
|
| 441 |
+
},
|
| 442 |
+
{
|
| 443 |
+
"epoch": 1.0448318804483188,
|
| 444 |
+
"eval_entropy": 0.5583065545489622,
|
| 445 |
+
"eval_loss": 0.5605642199516296,
|
| 446 |
+
"eval_mean_token_accuracy": 0.8439708411000496,
|
| 447 |
+
"eval_num_tokens": 980589.0,
|
| 448 |
+
"eval_runtime": 86.5422,
|
| 449 |
+
"eval_samples_per_second": 15.9,
|
| 450 |
+
"eval_steps_per_second": 1.987,
|
| 451 |
+
"step": 420
|
| 452 |
+
},
|
| 453 |
+
{
|
| 454 |
+
"entropy": 0.5671238023787737,
|
| 455 |
+
"epoch": 1.0946450809464507,
|
| 456 |
+
"grad_norm": 0.6882498264312744,
|
| 457 |
+
"learning_rate": 0.00020150112347025443,
|
| 458 |
+
"loss": 0.5077326774597168,
|
| 459 |
+
"mean_token_accuracy": 0.8489868573844432,
|
| 460 |
+
"num_tokens": 1027852.0,
|
| 461 |
+
"step": 440
|
| 462 |
+
},
|
| 463 |
+
{
|
| 464 |
+
"epoch": 1.0946450809464507,
|
| 465 |
+
"eval_entropy": 0.5868900277933409,
|
| 466 |
+
"eval_loss": 0.5602695345878601,
|
| 467 |
+
"eval_mean_token_accuracy": 0.8428842161977014,
|
| 468 |
+
"eval_num_tokens": 1027852.0,
|
| 469 |
+
"eval_runtime": 86.623,
|
| 470 |
+
"eval_samples_per_second": 15.885,
|
| 471 |
+
"eval_steps_per_second": 1.986,
|
| 472 |
+
"step": 440
|
| 473 |
+
},
|
| 474 |
+
{
|
| 475 |
+
"entropy": 0.5533561781048775,
|
| 476 |
+
"epoch": 1.1444582814445827,
|
| 477 |
+
"grad_norm": 0.7717723250389099,
|
| 478 |
+
"learning_rate": 0.0002014297192297181,
|
| 479 |
+
"loss": 0.4954517364501953,
|
| 480 |
+
"mean_token_accuracy": 0.8529035650193691,
|
| 481 |
+
"num_tokens": 1077649.0,
|
| 482 |
+
"step": 460
|
| 483 |
+
},
|
| 484 |
+
{
|
| 485 |
+
"epoch": 1.1444582814445827,
|
| 486 |
+
"eval_entropy": 0.5600803743961246,
|
| 487 |
+
"eval_loss": 0.5608077645301819,
|
| 488 |
+
"eval_mean_token_accuracy": 0.8445036771685578,
|
| 489 |
+
"eval_num_tokens": 1077649.0,
|
| 490 |
+
"eval_runtime": 86.1316,
|
| 491 |
+
"eval_samples_per_second": 15.976,
|
| 492 |
+
"eval_steps_per_second": 1.997,
|
| 493 |
+
"step": 460
|
| 494 |
+
},
|
| 495 |
+
{
|
| 496 |
+
"entropy": 0.5692154694348573,
|
| 497 |
+
"epoch": 1.1942714819427147,
|
| 498 |
+
"grad_norm": 0.7322827577590942,
|
| 499 |
+
"learning_rate": 0.0002013279593707117,
|
| 500 |
+
"loss": 0.505049467086792,
|
| 501 |
+
"mean_token_accuracy": 0.8551576808094978,
|
| 502 |
+
"num_tokens": 1124872.0,
|
| 503 |
+
"step": 480
|
| 504 |
+
},
|
| 505 |
+
{
|
| 506 |
+
"epoch": 1.1942714819427147,
|
| 507 |
+
"eval_entropy": 0.5732695829383162,
|
| 508 |
+
"eval_loss": 0.5594323873519897,
|
| 509 |
+
"eval_mean_token_accuracy": 0.8449713407560836,
|
| 510 |
+
"eval_num_tokens": 1124872.0,
|
| 511 |
+
"eval_runtime": 86.2726,
|
| 512 |
+
"eval_samples_per_second": 15.949,
|
| 513 |
+
"eval_steps_per_second": 1.994,
|
| 514 |
+
"step": 480
|
| 515 |
+
},
|
| 516 |
+
{
|
| 517 |
+
"entropy": 0.5817618492990733,
|
| 518 |
+
"epoch": 1.244084682440847,
|
| 519 |
+
"grad_norm": 1.1776764392852783,
|
| 520 |
+
"learning_rate": 0.0002011958745826208,
|
| 521 |
+
"loss": 0.5137609958648681,
|
| 522 |
+
"mean_token_accuracy": 0.8521522544324398,
|
| 523 |
+
"num_tokens": 1168698.0,
|
| 524 |
+
"step": 500
|
| 525 |
+
},
|
| 526 |
+
{
|
| 527 |
+
"epoch": 1.244084682440847,
|
| 528 |
+
"eval_entropy": 0.5662581343636957,
|
| 529 |
+
"eval_loss": 0.5595026016235352,
|
| 530 |
+
"eval_mean_token_accuracy": 0.8441977164773053,
|
| 531 |
+
"eval_num_tokens": 1168698.0,
|
| 532 |
+
"eval_runtime": 86.7261,
|
| 533 |
+
"eval_samples_per_second": 15.866,
|
| 534 |
+
"eval_steps_per_second": 1.983,
|
| 535 |
+
"step": 500
|
| 536 |
+
},
|
| 537 |
+
{
|
| 538 |
+
"entropy": 0.5712925456464291,
|
| 539 |
+
"epoch": 1.293897882938979,
|
| 540 |
+
"grad_norm": 0.7960361838340759,
|
| 541 |
+
"learning_rate": 0.0002010335047004159,
|
| 542 |
+
"loss": 0.5134767532348633,
|
| 543 |
+
"mean_token_accuracy": 0.8513577707111836,
|
| 544 |
+
"num_tokens": 1216679.0,
|
| 545 |
+
"step": 520
|
| 546 |
+
},
|
| 547 |
+
{
|
| 548 |
+
"epoch": 1.293897882938979,
|
| 549 |
+
"eval_entropy": 0.5441222797299541,
|
| 550 |
+
"eval_loss": 0.5535460114479065,
|
| 551 |
+
"eval_mean_token_accuracy": 0.8450886118550633,
|
| 552 |
+
"eval_num_tokens": 1216679.0,
|
| 553 |
+
"eval_runtime": 86.2675,
|
| 554 |
+
"eval_samples_per_second": 15.95,
|
| 555 |
+
"eval_steps_per_second": 1.994,
|
| 556 |
+
"step": 520
|
| 557 |
+
},
|
| 558 |
+
{
|
| 559 |
+
"entropy": 0.5787045754492283,
|
| 560 |
+
"epoch": 1.3437110834371109,
|
| 561 |
+
"grad_norm": 0.9205410480499268,
|
| 562 |
+
"learning_rate": 0.00020084089869263887,
|
| 563 |
+
"loss": 0.5119701862335205,
|
| 564 |
+
"mean_token_accuracy": 0.8503516331315041,
|
| 565 |
+
"num_tokens": 1261365.0,
|
| 566 |
+
"step": 540
|
| 567 |
+
},
|
| 568 |
+
{
|
| 569 |
+
"epoch": 1.3437110834371109,
|
| 570 |
+
"eval_entropy": 0.5744457827057949,
|
| 571 |
+
"eval_loss": 0.5514978766441345,
|
| 572 |
+
"eval_mean_token_accuracy": 0.845929987901865,
|
| 573 |
+
"eval_num_tokens": 1261365.0,
|
| 574 |
+
"eval_runtime": 86.2299,
|
| 575 |
+
"eval_samples_per_second": 15.957,
|
| 576 |
+
"eval_steps_per_second": 1.995,
|
| 577 |
+
"step": 540
|
| 578 |
+
},
|
| 579 |
+
{
|
| 580 |
+
"entropy": 0.5739392962306737,
|
| 581 |
+
"epoch": 1.3935242839352429,
|
| 582 |
+
"grad_norm": 0.7475653886795044,
|
| 583 |
+
"learning_rate": 0.00020061811464663464,
|
| 584 |
+
"loss": 0.5189042091369629,
|
| 585 |
+
"mean_token_accuracy": 0.8492388024926185,
|
| 586 |
+
"num_tokens": 1306879.0,
|
| 587 |
+
"step": 560
|
| 588 |
+
},
|
| 589 |
+
{
|
| 590 |
+
"epoch": 1.3935242839352429,
|
| 591 |
+
"eval_entropy": 0.6116398271433142,
|
| 592 |
+
"eval_loss": 0.551732063293457,
|
| 593 |
+
"eval_mean_token_accuracy": 0.8450756967067719,
|
| 594 |
+
"eval_num_tokens": 1306879.0,
|
| 595 |
+
"eval_runtime": 86.6081,
|
| 596 |
+
"eval_samples_per_second": 15.888,
|
| 597 |
+
"eval_steps_per_second": 1.986,
|
| 598 |
+
"step": 560
|
| 599 |
+
},
|
| 600 |
+
{
|
| 601 |
+
"entropy": 0.5755622573196888,
|
| 602 |
+
"epoch": 1.4433374844333748,
|
| 603 |
+
"grad_norm": 0.8218411803245544,
|
| 604 |
+
"learning_rate": 0.00020036521975103286,
|
| 605 |
+
"loss": 0.5106248378753662,
|
| 606 |
+
"mean_token_accuracy": 0.8506785586476326,
|
| 607 |
+
"num_tokens": 1353534.0,
|
| 608 |
+
"step": 580
|
| 609 |
+
},
|
| 610 |
+
{
|
| 611 |
+
"epoch": 1.4433374844333748,
|
| 612 |
+
"eval_entropy": 0.5906928708386976,
|
| 613 |
+
"eval_loss": 0.551278829574585,
|
| 614 |
+
"eval_mean_token_accuracy": 0.8462819308042526,
|
| 615 |
+
"eval_num_tokens": 1353534.0,
|
| 616 |
+
"eval_runtime": 86.5438,
|
| 617 |
+
"eval_samples_per_second": 15.899,
|
| 618 |
+
"eval_steps_per_second": 1.987,
|
| 619 |
+
"step": 580
|
| 620 |
+
},
|
| 621 |
+
{
|
| 622 |
+
"entropy": 0.5694822132587433,
|
| 623 |
+
"epoch": 1.4931506849315068,
|
| 624 |
+
"grad_norm": 0.8880652189254761,
|
| 625 |
+
"learning_rate": 0.00020008229027548475,
|
| 626 |
+
"loss": 0.5140334606170655,
|
| 627 |
+
"mean_token_accuracy": 0.8521522797644139,
|
| 628 |
+
"num_tokens": 1399537.0,
|
| 629 |
+
"step": 600
|
| 630 |
+
},
|
| 631 |
+
{
|
| 632 |
+
"epoch": 1.4931506849315068,
|
| 633 |
+
"eval_entropy": 0.5599641964532608,
|
| 634 |
+
"eval_loss": 0.5501875877380371,
|
| 635 |
+
"eval_mean_token_accuracy": 0.8467660788879838,
|
| 636 |
+
"eval_num_tokens": 1399537.0,
|
| 637 |
+
"eval_runtime": 86.6458,
|
| 638 |
+
"eval_samples_per_second": 15.881,
|
| 639 |
+
"eval_steps_per_second": 1.985,
|
| 640 |
+
"step": 600
|
| 641 |
+
},
|
| 642 |
+
{
|
| 643 |
+
"entropy": 0.5675108034163714,
|
| 644 |
+
"epoch": 1.5429638854296388,
|
| 645 |
+
"grad_norm": 0.837087094783783,
|
| 646 |
+
"learning_rate": 0.0001997694115476612,
|
| 647 |
+
"loss": 0.5099846363067627,
|
| 648 |
+
"mean_token_accuracy": 0.8543680295348167,
|
| 649 |
+
"num_tokens": 1448422.0,
|
| 650 |
+
"step": 620
|
| 651 |
+
},
|
| 652 |
+
{
|
| 653 |
+
"epoch": 1.5429638854296388,
|
| 654 |
+
"eval_entropy": 0.5728072581249614,
|
| 655 |
+
"eval_loss": 0.5445425510406494,
|
| 656 |
+
"eval_mean_token_accuracy": 0.8474342175001321,
|
| 657 |
+
"eval_num_tokens": 1448422.0,
|
| 658 |
+
"eval_runtime": 86.4859,
|
| 659 |
+
"eval_samples_per_second": 15.91,
|
| 660 |
+
"eval_steps_per_second": 1.989,
|
| 661 |
+
"step": 620
|
| 662 |
+
},
|
| 663 |
+
{
|
| 664 |
+
"entropy": 0.5700885068625212,
|
| 665 |
+
"epoch": 1.592777085927771,
|
| 666 |
+
"grad_norm": 0.6598765850067139,
|
| 667 |
+
"learning_rate": 0.000199426677927519,
|
| 668 |
+
"loss": 0.5122694969177246,
|
| 669 |
+
"mean_token_accuracy": 0.8519927568733692,
|
| 670 |
+
"num_tokens": 1495009.0,
|
| 671 |
+
"step": 640
|
| 672 |
+
},
|
| 673 |
+
{
|
| 674 |
+
"epoch": 1.592777085927771,
|
| 675 |
+
"eval_entropy": 0.5476993622128353,
|
| 676 |
+
"eval_loss": 0.5427973866462708,
|
| 677 |
+
"eval_mean_token_accuracy": 0.8478512147138285,
|
| 678 |
+
"eval_num_tokens": 1495009.0,
|
| 679 |
+
"eval_runtime": 86.4172,
|
| 680 |
+
"eval_samples_per_second": 15.923,
|
| 681 |
+
"eval_steps_per_second": 1.99,
|
| 682 |
+
"step": 640
|
| 683 |
+
},
|
| 684 |
+
{
|
| 685 |
+
"entropy": 0.5829229176044464,
|
| 686 |
+
"epoch": 1.6425902864259028,
|
| 687 |
+
"grad_norm": 0.6965194940567017,
|
| 688 |
+
"learning_rate": 0.00019905419277884342,
|
| 689 |
+
"loss": 0.5253659725189209,
|
| 690 |
+
"mean_token_accuracy": 0.8493309423327446,
|
| 691 |
+
"num_tokens": 1536932.0,
|
| 692 |
+
"step": 660
|
| 693 |
+
},
|
| 694 |
+
{
|
| 695 |
+
"epoch": 1.6425902864259028,
|
| 696 |
+
"eval_entropy": 0.5666290084983028,
|
| 697 |
+
"eval_loss": 0.5467478036880493,
|
| 698 |
+
"eval_mean_token_accuracy": 0.8479407703460649,
|
| 699 |
+
"eval_num_tokens": 1536932.0,
|
| 700 |
+
"eval_runtime": 86.4414,
|
| 701 |
+
"eval_samples_per_second": 15.918,
|
| 702 |
+
"eval_steps_per_second": 1.99,
|
| 703 |
+
"step": 660
|
| 704 |
+
},
|
| 705 |
+
{
|
| 706 |
+
"entropy": 0.5498311135917902,
|
| 707 |
+
"epoch": 1.692403486924035,
|
| 708 |
+
"grad_norm": 0.636583685874939,
|
| 709 |
+
"learning_rate": 0.00019865206843807482,
|
| 710 |
+
"loss": 0.49981012344360354,
|
| 711 |
+
"mean_token_accuracy": 0.8560848504304885,
|
| 712 |
+
"num_tokens": 1585718.0,
|
| 713 |
+
"step": 680
|
| 714 |
+
},
|
| 715 |
+
{
|
| 716 |
+
"epoch": 1.692403486924035,
|
| 717 |
+
"eval_entropy": 0.539117265406043,
|
| 718 |
+
"eval_loss": 0.53994220495224,
|
| 719 |
+
"eval_mean_token_accuracy": 0.8488582601380903,
|
| 720 |
+
"eval_num_tokens": 1585718.0,
|
| 721 |
+
"eval_runtime": 86.5296,
|
| 722 |
+
"eval_samples_per_second": 15.902,
|
| 723 |
+
"eval_steps_per_second": 1.988,
|
| 724 |
+
"step": 680
|
| 725 |
+
},
|
| 726 |
+
{
|
| 727 |
+
"entropy": 0.5543891470879316,
|
| 728 |
+
"epoch": 1.7422166874221667,
|
| 729 |
+
"grad_norm": 0.6068442463874817,
|
| 730 |
+
"learning_rate": 0.0001982204261804297,
|
| 731 |
+
"loss": 0.498047399520874,
|
| 732 |
+
"mean_token_accuracy": 0.8554679051041603,
|
| 733 |
+
"num_tokens": 1635718.0,
|
| 734 |
+
"step": 700
|
| 735 |
+
},
|
| 736 |
+
{
|
| 737 |
+
"epoch": 1.7422166874221667,
|
| 738 |
+
"eval_entropy": 0.5703774151760478,
|
| 739 |
+
"eval_loss": 0.5300245881080627,
|
| 740 |
+
"eval_mean_token_accuracy": 0.850798153946566,
|
| 741 |
+
"eval_num_tokens": 1635718.0,
|
| 742 |
+
"eval_runtime": 86.6456,
|
| 743 |
+
"eval_samples_per_second": 15.881,
|
| 744 |
+
"eval_steps_per_second": 1.985,
|
| 745 |
+
"step": 700
|
| 746 |
+
},
|
| 747 |
+
{
|
| 748 |
+
"entropy": 0.546524541825056,
|
| 749 |
+
"epoch": 1.792029887920299,
|
| 750 |
+
"grad_norm": 0.7274155020713806,
|
| 751 |
+
"learning_rate": 0.00019775939618332566,
|
| 752 |
+
"loss": 0.4988589286804199,
|
| 753 |
+
"mean_token_accuracy": 0.853422473371029,
|
| 754 |
+
"num_tokens": 1681291.0,
|
| 755 |
+
"step": 720
|
| 756 |
+
},
|
| 757 |
+
{
|
| 758 |
+
"epoch": 1.792029887920299,
|
| 759 |
+
"eval_entropy": 0.5614905688305234,
|
| 760 |
+
"eval_loss": 0.5350332260131836,
|
| 761 |
+
"eval_mean_token_accuracy": 0.8492204359797544,
|
| 762 |
+
"eval_num_tokens": 1681291.0,
|
| 763 |
+
"eval_runtime": 86.7581,
|
| 764 |
+
"eval_samples_per_second": 15.86,
|
| 765 |
+
"eval_steps_per_second": 1.983,
|
| 766 |
+
"step": 720
|
| 767 |
+
},
|
| 768 |
+
{
|
| 769 |
+
"entropy": 0.5519792139530182,
|
| 770 |
+
"epoch": 1.841843088418431,
|
| 771 |
+
"grad_norm": 0.663466215133667,
|
| 772 |
+
"learning_rate": 0.00019726911748712167,
|
| 773 |
+
"loss": 0.5099314212799072,
|
| 774 |
+
"mean_token_accuracy": 0.848412600159645,
|
| 775 |
+
"num_tokens": 1729102.0,
|
| 776 |
+
"step": 740
|
| 777 |
+
},
|
| 778 |
+
{
|
| 779 |
+
"epoch": 1.841843088418431,
|
| 780 |
+
"eval_entropy": 0.5583519090053647,
|
| 781 |
+
"eval_loss": 0.530483603477478,
|
| 782 |
+
"eval_mean_token_accuracy": 0.8500003374593202,
|
| 783 |
+
"eval_num_tokens": 1729102.0,
|
| 784 |
+
"eval_runtime": 86.3961,
|
| 785 |
+
"eval_samples_per_second": 15.927,
|
| 786 |
+
"eval_steps_per_second": 1.991,
|
| 787 |
+
"step": 740
|
| 788 |
+
},
|
| 789 |
+
{
|
| 790 |
+
"entropy": 0.5454779766499996,
|
| 791 |
+
"epoch": 1.891656288916563,
|
| 792 |
+
"grad_norm": 0.890394926071167,
|
| 793 |
+
"learning_rate": 0.00019674973795318548,
|
| 794 |
+
"loss": 0.4931994915008545,
|
| 795 |
+
"mean_token_accuracy": 0.8540832489728928,
|
| 796 |
+
"num_tokens": 1773578.0,
|
| 797 |
+
"step": 760
|
| 798 |
+
},
|
| 799 |
+
{
|
| 800 |
+
"epoch": 1.891656288916563,
|
| 801 |
+
"eval_entropy": 0.572755502406941,
|
| 802 |
+
"eval_loss": 0.5415747761726379,
|
| 803 |
+
"eval_mean_token_accuracy": 0.8444425803284312,
|
| 804 |
+
"eval_num_tokens": 1773578.0,
|
| 805 |
+
"eval_runtime": 86.4323,
|
| 806 |
+
"eval_samples_per_second": 15.92,
|
| 807 |
+
"eval_steps_per_second": 1.99,
|
| 808 |
+
"step": 760
|
| 809 |
+
},
|
| 810 |
+
{
|
| 811 |
+
"entropy": 0.5392089951783419,
|
| 812 |
+
"epoch": 1.9414694894146949,
|
| 813 |
+
"grad_norm": 0.632411777973175,
|
| 814 |
+
"learning_rate": 0.00019620141421930058,
|
| 815 |
+
"loss": 0.4957888603210449,
|
| 816 |
+
"mean_token_accuracy": 0.8549866065382957,
|
| 817 |
+
"num_tokens": 1821725.0,
|
| 818 |
+
"step": 780
|
| 819 |
+
},
|
| 820 |
+
{
|
| 821 |
+
"epoch": 1.9414694894146949,
|
| 822 |
+
"eval_entropy": 0.540764772961306,
|
| 823 |
+
"eval_loss": 0.5327216386795044,
|
| 824 |
+
"eval_mean_token_accuracy": 0.850631088364956,
|
| 825 |
+
"eval_num_tokens": 1821725.0,
|
| 826 |
+
"eval_runtime": 86.8097,
|
| 827 |
+
"eval_samples_per_second": 15.851,
|
| 828 |
+
"eval_steps_per_second": 1.981,
|
| 829 |
+
"step": 780
|
| 830 |
+
},
|
| 831 |
+
{
|
| 832 |
+
"entropy": 0.5674678739160299,
|
| 833 |
+
"epoch": 1.9912826899128269,
|
| 834 |
+
"grad_norm": 0.6958843469619751,
|
| 835 |
+
"learning_rate": 0.0001956243116524263,
|
| 836 |
+
"loss": 0.504389762878418,
|
| 837 |
+
"mean_token_accuracy": 0.8527948908507824,
|
| 838 |
+
"num_tokens": 1868431.0,
|
| 839 |
+
"step": 800
|
| 840 |
+
},
|
| 841 |
+
{
|
| 842 |
+
"epoch": 1.9912826899128269,
|
| 843 |
+
"eval_entropy": 0.530262403190136,
|
| 844 |
+
"eval_loss": 0.5308871865272522,
|
| 845 |
+
"eval_mean_token_accuracy": 0.8522498046242913,
|
| 846 |
+
"eval_num_tokens": 1868431.0,
|
| 847 |
+
"eval_runtime": 86.7942,
|
| 848 |
+
"eval_samples_per_second": 15.854,
|
| 849 |
+
"eval_steps_per_second": 1.982,
|
| 850 |
+
"step": 800
|
| 851 |
+
},
|
| 852 |
+
{
|
| 853 |
+
"entropy": 0.4742849511213792,
|
| 854 |
+
"epoch": 2.0398505603985058,
|
| 855 |
+
"grad_norm": 0.6941492557525635,
|
| 856 |
+
"learning_rate": 0.00019501860429882556,
|
| 857 |
+
"loss": 0.418599271774292,
|
| 858 |
+
"mean_token_accuracy": 0.8748210859604371,
|
| 859 |
+
"num_tokens": 1915280.0,
|
| 860 |
+
"step": 820
|
| 861 |
+
},
|
| 862 |
+
{
|
| 863 |
+
"epoch": 2.0398505603985058,
|
| 864 |
+
"eval_entropy": 0.504602165069691,
|
| 865 |
+
"eval_loss": 0.542878270149231,
|
| 866 |
+
"eval_mean_token_accuracy": 0.8507604484641275,
|
| 867 |
+
"eval_num_tokens": 1915280.0,
|
| 868 |
+
"eval_runtime": 86.7841,
|
| 869 |
+
"eval_samples_per_second": 15.855,
|
| 870 |
+
"eval_steps_per_second": 1.982,
|
| 871 |
+
"step": 820
|
| 872 |
+
},
|
| 873 |
+
{
|
| 874 |
+
"entropy": 0.45857742577791216,
|
| 875 |
+
"epoch": 2.0896637608966375,
|
| 876 |
+
"grad_norm": 0.5791997909545898,
|
| 877 |
+
"learning_rate": 0.00019438447483157478,
|
| 878 |
+
"loss": 0.399777889251709,
|
| 879 |
+
"mean_token_accuracy": 0.8754058346152306,
|
| 880 |
+
"num_tokens": 1965306.0,
|
| 881 |
+
"step": 840
|
| 882 |
+
},
|
| 883 |
+
{
|
| 884 |
+
"epoch": 2.0896637608966375,
|
| 885 |
+
"eval_entropy": 0.5028848362176918,
|
| 886 |
+
"eval_loss": 0.5356478095054626,
|
| 887 |
+
"eval_mean_token_accuracy": 0.8525635412959165,
|
| 888 |
+
"eval_num_tokens": 1965306.0,
|
| 889 |
+
"eval_runtime": 86.6707,
|
| 890 |
+
"eval_samples_per_second": 15.876,
|
| 891 |
+
"eval_steps_per_second": 1.985,
|
| 892 |
+
"step": 840
|
| 893 |
+
},
|
| 894 |
+
{
|
| 895 |
+
"entropy": 0.4869446292519569,
|
| 896 |
+
"epoch": 2.1394769613947697,
|
| 897 |
+
"grad_norm": 0.6483516693115234,
|
| 898 |
+
"learning_rate": 0.00019372211449547223,
|
| 899 |
+
"loss": 0.40715818405151366,
|
| 900 |
+
"mean_token_accuracy": 0.875113020837307,
|
| 901 |
+
"num_tokens": 2008562.0,
|
| 902 |
+
"step": 860
|
| 903 |
+
},
|
| 904 |
+
{
|
| 905 |
+
"epoch": 2.1394769613947697,
|
| 906 |
+
"eval_entropy": 0.4928991326759028,
|
| 907 |
+
"eval_loss": 0.5419561862945557,
|
| 908 |
+
"eval_mean_token_accuracy": 0.8516040146350861,
|
| 909 |
+
"eval_num_tokens": 2008562.0,
|
| 910 |
+
"eval_runtime": 87.0686,
|
| 911 |
+
"eval_samples_per_second": 15.804,
|
| 912 |
+
"eval_steps_per_second": 1.975,
|
| 913 |
+
"step": 860
|
| 914 |
+
},
|
| 915 |
+
{
|
| 916 |
+
"entropy": 0.45819590501487256,
|
| 917 |
+
"epoch": 2.1892901618929015,
|
| 918 |
+
"grad_norm": 0.6661920547485352,
|
| 919 |
+
"learning_rate": 0.00019303172304936108,
|
| 920 |
+
"loss": 0.39511430263519287,
|
| 921 |
+
"mean_token_accuracy": 0.8780680045485496,
|
| 922 |
+
"num_tokens": 2056474.0,
|
| 923 |
+
"step": 880
|
| 924 |
+
},
|
| 925 |
+
{
|
| 926 |
+
"epoch": 2.1892901618929015,
|
| 927 |
+
"eval_entropy": 0.48602560647698334,
|
| 928 |
+
"eval_loss": 0.5436084866523743,
|
| 929 |
+
"eval_mean_token_accuracy": 0.8500938470973525,
|
| 930 |
+
"eval_num_tokens": 2056474.0,
|
| 931 |
+
"eval_runtime": 86.6809,
|
| 932 |
+
"eval_samples_per_second": 15.874,
|
| 933 |
+
"eval_steps_per_second": 1.984,
|
| 934 |
+
"step": 880
|
| 935 |
+
},
|
| 936 |
+
{
|
| 937 |
+
"entropy": 0.4780638810247183,
|
| 938 |
+
"epoch": 2.2391033623910337,
|
| 939 |
+
"grad_norm": 0.6870484352111816,
|
| 940 |
+
"learning_rate": 0.0001923135087058851,
|
| 941 |
+
"loss": 0.4061615467071533,
|
| 942 |
+
"mean_token_accuracy": 0.8766494184732437,
|
| 943 |
+
"num_tokens": 2103543.0,
|
| 944 |
+
"step": 900
|
| 945 |
+
},
|
| 946 |
+
{
|
| 947 |
+
"epoch": 2.2391033623910337,
|
| 948 |
+
"eval_entropy": 0.48236206035281337,
|
| 949 |
+
"eval_loss": 0.5446090698242188,
|
| 950 |
+
"eval_mean_token_accuracy": 0.8507725513258646,
|
| 951 |
+
"eval_num_tokens": 2103543.0,
|
| 952 |
+
"eval_runtime": 86.7398,
|
| 953 |
+
"eval_samples_per_second": 15.864,
|
| 954 |
+
"eval_steps_per_second": 1.983,
|
| 955 |
+
"step": 900
|
| 956 |
+
},
|
| 957 |
+
{
|
| 958 |
+
"entropy": 0.463029869645834,
|
| 959 |
+
"epoch": 2.2889165628891655,
|
| 960 |
+
"grad_norm": 0.6894590854644775,
|
| 961 |
+
"learning_rate": 0.00019156768806869427,
|
| 962 |
+
"loss": 0.39602413177490237,
|
| 963 |
+
"mean_token_accuracy": 0.876420046389103,
|
| 964 |
+
"num_tokens": 2147861.0,
|
| 965 |
+
"step": 920
|
| 966 |
+
},
|
| 967 |
+
{
|
| 968 |
+
"epoch": 2.2889165628891655,
|
| 969 |
+
"eval_entropy": 0.4904779093556626,
|
| 970 |
+
"eval_loss": 0.5404934287071228,
|
| 971 |
+
"eval_mean_token_accuracy": 0.852238280828609,
|
| 972 |
+
"eval_num_tokens": 2147861.0,
|
| 973 |
+
"eval_runtime": 86.5348,
|
| 974 |
+
"eval_samples_per_second": 15.901,
|
| 975 |
+
"eval_steps_per_second": 1.988,
|
| 976 |
+
"step": 920
|
| 977 |
+
},
|
| 978 |
+
{
|
| 979 |
+
"entropy": 0.4817025110125542,
|
| 980 |
+
"epoch": 2.3387297633872977,
|
| 981 |
+
"grad_norm": 0.7756227254867554,
|
| 982 |
+
"learning_rate": 0.00019079448606712033,
|
| 983 |
+
"loss": 0.4177968502044678,
|
| 984 |
+
"mean_token_accuracy": 0.8712256088852882,
|
| 985 |
+
"num_tokens": 2190561.0,
|
| 986 |
+
"step": 940
|
| 987 |
+
},
|
| 988 |
+
{
|
| 989 |
+
"epoch": 2.3387297633872977,
|
| 990 |
+
"eval_entropy": 0.5153802815218305,
|
| 991 |
+
"eval_loss": 0.5424937605857849,
|
| 992 |
+
"eval_mean_token_accuracy": 0.8506565759348315,
|
| 993 |
+
"eval_num_tokens": 2190561.0,
|
| 994 |
+
"eval_runtime": 86.8973,
|
| 995 |
+
"eval_samples_per_second": 15.835,
|
| 996 |
+
"eval_steps_per_second": 1.979,
|
| 997 |
+
"step": 940
|
| 998 |
+
},
|
| 999 |
+
{
|
| 1000 |
+
"entropy": 0.46456389091908934,
|
| 1001 |
+
"epoch": 2.3885429638854294,
|
| 1002 |
+
"grad_norm": 1.2000319957733154,
|
| 1003 |
+
"learning_rate": 0.00018999413588834105,
|
| 1004 |
+
"loss": 0.4084665775299072,
|
| 1005 |
+
"mean_token_accuracy": 0.8750658087432385,
|
| 1006 |
+
"num_tokens": 2239412.0,
|
| 1007 |
+
"step": 960
|
| 1008 |
+
},
|
| 1009 |
+
{
|
| 1010 |
+
"epoch": 2.3885429638854294,
|
| 1011 |
+
"eval_entropy": 0.4849439303195754,
|
| 1012 |
+
"eval_loss": 0.545662522315979,
|
| 1013 |
+
"eval_mean_token_accuracy": 0.8491013112456299,
|
| 1014 |
+
"eval_num_tokens": 2239412.0,
|
| 1015 |
+
"eval_runtime": 86.9049,
|
| 1016 |
+
"eval_samples_per_second": 15.833,
|
| 1017 |
+
"eval_steps_per_second": 1.979,
|
| 1018 |
+
"step": 960
|
| 1019 |
+
},
|
| 1020 |
+
{
|
| 1021 |
+
"entropy": 0.4857471022754908,
|
| 1022 |
+
"epoch": 2.4383561643835616,
|
| 1023 |
+
"grad_norm": 0.9696341753005981,
|
| 1024 |
+
"learning_rate": 0.0001891668789070541,
|
| 1025 |
+
"loss": 0.4149796962738037,
|
| 1026 |
+
"mean_token_accuracy": 0.8704176343977451,
|
| 1027 |
+
"num_tokens": 2286283.0,
|
| 1028 |
+
"step": 980
|
| 1029 |
+
},
|
| 1030 |
+
{
|
| 1031 |
+
"epoch": 2.4383561643835616,
|
| 1032 |
+
"eval_entropy": 0.4872790058684904,
|
| 1033 |
+
"eval_loss": 0.5412707924842834,
|
| 1034 |
+
"eval_mean_token_accuracy": 0.8509329602468846,
|
| 1035 |
+
"eval_num_tokens": 2286283.0,
|
| 1036 |
+
"eval_runtime": 86.7846,
|
| 1037 |
+
"eval_samples_per_second": 15.855,
|
| 1038 |
+
"eval_steps_per_second": 1.982,
|
| 1039 |
+
"step": 980
|
| 1040 |
+
},
|
| 1041 |
+
{
|
| 1042 |
+
"entropy": 0.4727417893707752,
|
| 1043 |
+
"epoch": 2.488169364881694,
|
| 1044 |
+
"grad_norm": 0.7852500677108765,
|
| 1045 |
+
"learning_rate": 0.0001883129646126818,
|
| 1046 |
+
"loss": 0.4142886161804199,
|
| 1047 |
+
"mean_token_accuracy": 0.8712429471313954,
|
| 1048 |
+
"num_tokens": 2333733.0,
|
| 1049 |
+
"step": 1000
|
| 1050 |
+
},
|
| 1051 |
+
{
|
| 1052 |
+
"epoch": 2.488169364881694,
|
| 1053 |
+
"eval_entropy": 0.5386548059624295,
|
| 1054 |
+
"eval_loss": 0.536101222038269,
|
| 1055 |
+
"eval_mean_token_accuracy": 0.8499491239009902,
|
| 1056 |
+
"eval_num_tokens": 2333733.0,
|
| 1057 |
+
"eval_runtime": 86.9501,
|
| 1058 |
+
"eval_samples_per_second": 15.825,
|
| 1059 |
+
"eval_steps_per_second": 1.978,
|
| 1060 |
+
"step": 1000
|
| 1061 |
+
}
|
| 1062 |
+
],
|
| 1063 |
+
"logging_steps": 20,
|
| 1064 |
+
"max_steps": 4020,
|
| 1065 |
+
"num_input_tokens_seen": 0,
|
| 1066 |
+
"num_train_epochs": 10,
|
| 1067 |
+
"save_steps": 20,
|
| 1068 |
+
"stateful_callbacks": {
|
| 1069 |
+
"TrainerControl": {
|
| 1070 |
+
"args": {
|
| 1071 |
+
"should_epoch_stop": false,
|
| 1072 |
+
"should_evaluate": false,
|
| 1073 |
+
"should_log": false,
|
| 1074 |
+
"should_save": true,
|
| 1075 |
+
"should_training_stop": false
|
| 1076 |
+
},
|
| 1077 |
+
"attributes": {}
|
| 1078 |
+
}
|
| 1079 |
+
},
|
| 1080 |
+
"total_flos": 9.859037950771814e+16,
|
| 1081 |
+
"train_batch_size": 4,
|
| 1082 |
+
"trial_name": null,
|
| 1083 |
+
"trial_params": null
|
| 1084 |
+
}
|
overgeneralisation_original_Swedish/Qwen3.5-4B-Base_overgeneralisation_splits_original_features_train_overgeneralisation_splits_original_features_test1/checkpoint-1020/README.md
ADDED
|
@@ -0,0 +1,209 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
---
|
| 2 |
+
base_model: Qwen/Qwen3.5-4B-Base
|
| 3 |
+
library_name: peft
|
| 4 |
+
pipeline_tag: text-generation
|
| 5 |
+
tags:
|
| 6 |
+
- base_model:adapter:Qwen/Qwen3.5-4B-Base
|
| 7 |
+
- lora
|
| 8 |
+
- sft
|
| 9 |
+
- transformers
|
| 10 |
+
- trl
|
| 11 |
+
---
|
| 12 |
+
|
| 13 |
+
# Model Card for Model ID
|
| 14 |
+
|
| 15 |
+
<!-- Provide a quick summary of what the model is/does. -->
|
| 16 |
+
|
| 17 |
+
|
| 18 |
+
|
| 19 |
+
## Model Details
|
| 20 |
+
|
| 21 |
+
### Model Description
|
| 22 |
+
|
| 23 |
+
<!-- Provide a longer summary of what this model is. -->
|
| 24 |
+
|
| 25 |
+
|
| 26 |
+
|
| 27 |
+
- **Developed by:** [More Information Needed]
|
| 28 |
+
- **Funded by [optional]:** [More Information Needed]
|
| 29 |
+
- **Shared by [optional]:** [More Information Needed]
|
| 30 |
+
- **Model type:** [More Information Needed]
|
| 31 |
+
- **Language(s) (NLP):** [More Information Needed]
|
| 32 |
+
- **License:** [More Information Needed]
|
| 33 |
+
- **Finetuned from model [optional]:** [More Information Needed]
|
| 34 |
+
|
| 35 |
+
### Model Sources [optional]
|
| 36 |
+
|
| 37 |
+
<!-- Provide the basic links for the model. -->
|
| 38 |
+
|
| 39 |
+
- **Repository:** [More Information Needed]
|
| 40 |
+
- **Paper [optional]:** [More Information Needed]
|
| 41 |
+
- **Demo [optional]:** [More Information Needed]
|
| 42 |
+
|
| 43 |
+
## Uses
|
| 44 |
+
|
| 45 |
+
<!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
|
| 46 |
+
|
| 47 |
+
### Direct Use
|
| 48 |
+
|
| 49 |
+
<!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
|
| 50 |
+
|
| 51 |
+
[More Information Needed]
|
| 52 |
+
|
| 53 |
+
### Downstream Use [optional]
|
| 54 |
+
|
| 55 |
+
<!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
|
| 56 |
+
|
| 57 |
+
[More Information Needed]
|
| 58 |
+
|
| 59 |
+
### Out-of-Scope Use
|
| 60 |
+
|
| 61 |
+
<!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
|
| 62 |
+
|
| 63 |
+
[More Information Needed]
|
| 64 |
+
|
| 65 |
+
## Bias, Risks, and Limitations
|
| 66 |
+
|
| 67 |
+
<!-- This section is meant to convey both technical and sociotechnical limitations. -->
|
| 68 |
+
|
| 69 |
+
[More Information Needed]
|
| 70 |
+
|
| 71 |
+
### Recommendations
|
| 72 |
+
|
| 73 |
+
<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
|
| 74 |
+
|
| 75 |
+
Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
|
| 76 |
+
|
| 77 |
+
## How to Get Started with the Model
|
| 78 |
+
|
| 79 |
+
Use the code below to get started with the model.
|
| 80 |
+
|
| 81 |
+
[More Information Needed]
|
| 82 |
+
|
| 83 |
+
## Training Details
|
| 84 |
+
|
| 85 |
+
### Training Data
|
| 86 |
+
|
| 87 |
+
<!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
|
| 88 |
+
|
| 89 |
+
[More Information Needed]
|
| 90 |
+
|
| 91 |
+
### Training Procedure
|
| 92 |
+
|
| 93 |
+
<!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
|
| 94 |
+
|
| 95 |
+
#### Preprocessing [optional]
|
| 96 |
+
|
| 97 |
+
[More Information Needed]
|
| 98 |
+
|
| 99 |
+
|
| 100 |
+
#### Training Hyperparameters
|
| 101 |
+
|
| 102 |
+
- **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
|
| 103 |
+
|
| 104 |
+
#### Speeds, Sizes, Times [optional]
|
| 105 |
+
|
| 106 |
+
<!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
|
| 107 |
+
|
| 108 |
+
[More Information Needed]
|
| 109 |
+
|
| 110 |
+
## Evaluation
|
| 111 |
+
|
| 112 |
+
<!-- This section describes the evaluation protocols and provides the results. -->
|
| 113 |
+
|
| 114 |
+
### Testing Data, Factors & Metrics
|
| 115 |
+
|
| 116 |
+
#### Testing Data
|
| 117 |
+
|
| 118 |
+
<!-- This should link to a Dataset Card if possible. -->
|
| 119 |
+
|
| 120 |
+
[More Information Needed]
|
| 121 |
+
|
| 122 |
+
#### Factors
|
| 123 |
+
|
| 124 |
+
<!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
|
| 125 |
+
|
| 126 |
+
[More Information Needed]
|
| 127 |
+
|
| 128 |
+
#### Metrics
|
| 129 |
+
|
| 130 |
+
<!-- These are the evaluation metrics being used, ideally with a description of why. -->
|
| 131 |
+
|
| 132 |
+
[More Information Needed]
|
| 133 |
+
|
| 134 |
+
### Results
|
| 135 |
+
|
| 136 |
+
[More Information Needed]
|
| 137 |
+
|
| 138 |
+
#### Summary
|
| 139 |
+
|
| 140 |
+
|
| 141 |
+
|
| 142 |
+
## Model Examination [optional]
|
| 143 |
+
|
| 144 |
+
<!-- Relevant interpretability work for the model goes here -->
|
| 145 |
+
|
| 146 |
+
[More Information Needed]
|
| 147 |
+
|
| 148 |
+
## Environmental Impact
|
| 149 |
+
|
| 150 |
+
<!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
|
| 151 |
+
|
| 152 |
+
Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
|
| 153 |
+
|
| 154 |
+
- **Hardware Type:** [More Information Needed]
|
| 155 |
+
- **Hours used:** [More Information Needed]
|
| 156 |
+
- **Cloud Provider:** [More Information Needed]
|
| 157 |
+
- **Compute Region:** [More Information Needed]
|
| 158 |
+
- **Carbon Emitted:** [More Information Needed]
|
| 159 |
+
|
| 160 |
+
## Technical Specifications [optional]
|
| 161 |
+
|
| 162 |
+
### Model Architecture and Objective
|
| 163 |
+
|
| 164 |
+
[More Information Needed]
|
| 165 |
+
|
| 166 |
+
### Compute Infrastructure
|
| 167 |
+
|
| 168 |
+
[More Information Needed]
|
| 169 |
+
|
| 170 |
+
#### Hardware
|
| 171 |
+
|
| 172 |
+
[More Information Needed]
|
| 173 |
+
|
| 174 |
+
#### Software
|
| 175 |
+
|
| 176 |
+
[More Information Needed]
|
| 177 |
+
|
| 178 |
+
## Citation [optional]
|
| 179 |
+
|
| 180 |
+
<!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
|
| 181 |
+
|
| 182 |
+
**BibTeX:**
|
| 183 |
+
|
| 184 |
+
[More Information Needed]
|
| 185 |
+
|
| 186 |
+
**APA:**
|
| 187 |
+
|
| 188 |
+
[More Information Needed]
|
| 189 |
+
|
| 190 |
+
## Glossary [optional]
|
| 191 |
+
|
| 192 |
+
<!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
|
| 193 |
+
|
| 194 |
+
[More Information Needed]
|
| 195 |
+
|
| 196 |
+
## More Information [optional]
|
| 197 |
+
|
| 198 |
+
[More Information Needed]
|
| 199 |
+
|
| 200 |
+
## Model Card Authors [optional]
|
| 201 |
+
|
| 202 |
+
[More Information Needed]
|
| 203 |
+
|
| 204 |
+
## Model Card Contact
|
| 205 |
+
|
| 206 |
+
[More Information Needed]
|
| 207 |
+
### Framework versions
|
| 208 |
+
|
| 209 |
+
- PEFT 0.18.1
|
overgeneralisation_original_Swedish/Qwen3.5-4B-Base_overgeneralisation_splits_original_features_train_overgeneralisation_splits_original_features_test1/checkpoint-1020/adapter_config.json
ADDED
|
@@ -0,0 +1,46 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
{
|
| 2 |
+
"alora_invocation_tokens": null,
|
| 3 |
+
"alpha_pattern": {},
|
| 4 |
+
"arrow_config": null,
|
| 5 |
+
"auto_mapping": null,
|
| 6 |
+
"base_model_name_or_path": "Qwen/Qwen3.5-4B-Base",
|
| 7 |
+
"bias": "none",
|
| 8 |
+
"corda_config": null,
|
| 9 |
+
"ensure_weight_tying": false,
|
| 10 |
+
"eva_config": null,
|
| 11 |
+
"exclude_modules": null,
|
| 12 |
+
"fan_in_fan_out": false,
|
| 13 |
+
"inference_mode": true,
|
| 14 |
+
"init_lora_weights": true,
|
| 15 |
+
"layer_replication": null,
|
| 16 |
+
"layers_pattern": null,
|
| 17 |
+
"layers_to_transform": null,
|
| 18 |
+
"loftq_config": {},
|
| 19 |
+
"lora_alpha": 256,
|
| 20 |
+
"lora_bias": false,
|
| 21 |
+
"lora_dropout": 0.0005183818805460705,
|
| 22 |
+
"megatron_config": null,
|
| 23 |
+
"megatron_core": "megatron.core",
|
| 24 |
+
"modules_to_save": null,
|
| 25 |
+
"peft_type": "LORA",
|
| 26 |
+
"peft_version": "0.18.1",
|
| 27 |
+
"qalora_group_size": 16,
|
| 28 |
+
"r": 128,
|
| 29 |
+
"rank_pattern": {},
|
| 30 |
+
"revision": null,
|
| 31 |
+
"target_modules": [
|
| 32 |
+
"up_proj",
|
| 33 |
+
"q_proj",
|
| 34 |
+
"o_proj",
|
| 35 |
+
"v_proj",
|
| 36 |
+
"k_proj",
|
| 37 |
+
"gate_proj",
|
| 38 |
+
"down_proj"
|
| 39 |
+
],
|
| 40 |
+
"target_parameters": null,
|
| 41 |
+
"task_type": "CAUSAL_LM",
|
| 42 |
+
"trainable_token_indices": null,
|
| 43 |
+
"use_dora": false,
|
| 44 |
+
"use_qalora": false,
|
| 45 |
+
"use_rslora": false
|
| 46 |
+
}
|
overgeneralisation_original_Swedish/Qwen3.5-4B-Base_overgeneralisation_splits_original_features_train_overgeneralisation_splits_original_features_test1/checkpoint-1020/chat_template.jinja
ADDED
|
@@ -0,0 +1,154 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
{%- set image_count = namespace(value=0) %}
|
| 2 |
+
{%- set video_count = namespace(value=0) %}
|
| 3 |
+
{%- macro render_content(content, do_vision_count, is_system_content=false) %}
|
| 4 |
+
{%- if content is string %}
|
| 5 |
+
{{- content }}
|
| 6 |
+
{%- elif content is iterable and content is not mapping %}
|
| 7 |
+
{%- for item in content %}
|
| 8 |
+
{%- if 'image' in item or 'image_url' in item or item.type == 'image' %}
|
| 9 |
+
{%- if is_system_content %}
|
| 10 |
+
{{- raise_exception('System message cannot contain images.') }}
|
| 11 |
+
{%- endif %}
|
| 12 |
+
{%- if do_vision_count %}
|
| 13 |
+
{%- set image_count.value = image_count.value + 1 %}
|
| 14 |
+
{%- endif %}
|
| 15 |
+
{%- if add_vision_id %}
|
| 16 |
+
{{- 'Picture ' ~ image_count.value ~ ': ' }}
|
| 17 |
+
{%- endif %}
|
| 18 |
+
{{- '<|vision_start|><|image_pad|><|vision_end|>' }}
|
| 19 |
+
{%- elif 'video' in item or item.type == 'video' %}
|
| 20 |
+
{%- if is_system_content %}
|
| 21 |
+
{{- raise_exception('System message cannot contain videos.') }}
|
| 22 |
+
{%- endif %}
|
| 23 |
+
{%- if do_vision_count %}
|
| 24 |
+
{%- set video_count.value = video_count.value + 1 %}
|
| 25 |
+
{%- endif %}
|
| 26 |
+
{%- if add_vision_id %}
|
| 27 |
+
{{- 'Video ' ~ video_count.value ~ ': ' }}
|
| 28 |
+
{%- endif %}
|
| 29 |
+
{{- '<|vision_start|><|video_pad|><|vision_end|>' }}
|
| 30 |
+
{%- elif 'text' in item %}
|
| 31 |
+
{{- item.text }}
|
| 32 |
+
{%- else %}
|
| 33 |
+
{{- raise_exception('Unexpected item type in content.') }}
|
| 34 |
+
{%- endif %}
|
| 35 |
+
{%- endfor %}
|
| 36 |
+
{%- elif content is none or content is undefined %}
|
| 37 |
+
{{- '' }}
|
| 38 |
+
{%- else %}
|
| 39 |
+
{{- raise_exception('Unexpected content type.') }}
|
| 40 |
+
{%- endif %}
|
| 41 |
+
{%- endmacro %}
|
| 42 |
+
{%- if not messages %}
|
| 43 |
+
{{- raise_exception('No messages provided.') }}
|
| 44 |
+
{%- endif %}
|
| 45 |
+
{%- if tools and tools is iterable and tools is not mapping %}
|
| 46 |
+
{{- '<|im_start|>system\n' }}
|
| 47 |
+
{{- "# Tools\n\nYou have access to the following functions:\n\n<tools>" }}
|
| 48 |
+
{%- for tool in tools %}
|
| 49 |
+
{{- "\n" }}
|
| 50 |
+
{{- tool | tojson }}
|
| 51 |
+
{%- endfor %}
|
| 52 |
+
{{- "\n</tools>" }}
|
| 53 |
+
{{- '\n\nIf you choose to call a function ONLY reply in the following format with NO suffix:\n\n<tool_call>\n<function=example_function_name>\n<parameter=example_parameter_1>\nvalue_1\n</parameter>\n<parameter=example_parameter_2>\nThis is the value for the second parameter\nthat can span\nmultiple lines\n</parameter>\n</function>\n</tool_call>\n\n<IMPORTANT>\nReminder:\n- Function calls MUST follow the specified format: an inner <function=...></function> block must be nested within <tool_call></tool_call> XML tags\n- Required parameters MUST be specified\n- You may provide optional reasoning for your function call in natural language BEFORE the function call, but NOT after\n- If there is no function call available, answer the question like normal with your current knowledge and do not tell the user about function calls\n</IMPORTANT>' }}
|
| 54 |
+
{%- if messages[0].role == 'system' %}
|
| 55 |
+
{%- set content = render_content(messages[0].content, false, true)|trim %}
|
| 56 |
+
{%- if content %}
|
| 57 |
+
{{- '\n\n' + content }}
|
| 58 |
+
{%- endif %}
|
| 59 |
+
{%- endif %}
|
| 60 |
+
{{- '<|im_end|>\n' }}
|
| 61 |
+
{%- else %}
|
| 62 |
+
{%- if messages[0].role == 'system' %}
|
| 63 |
+
{%- set content = render_content(messages[0].content, false, true)|trim %}
|
| 64 |
+
{{- '<|im_start|>system\n' + content + '<|im_end|>\n' }}
|
| 65 |
+
{%- endif %}
|
| 66 |
+
{%- endif %}
|
| 67 |
+
{%- set ns = namespace(multi_step_tool=true, last_query_index=messages|length - 1) %}
|
| 68 |
+
{%- for message in messages[::-1] %}
|
| 69 |
+
{%- set index = (messages|length - 1) - loop.index0 %}
|
| 70 |
+
{%- if ns.multi_step_tool and message.role == "user" %}
|
| 71 |
+
{%- set content = render_content(message.content, false)|trim %}
|
| 72 |
+
{%- if not(content.startswith('<tool_response>') and content.endswith('</tool_response>')) %}
|
| 73 |
+
{%- set ns.multi_step_tool = false %}
|
| 74 |
+
{%- set ns.last_query_index = index %}
|
| 75 |
+
{%- endif %}
|
| 76 |
+
{%- endif %}
|
| 77 |
+
{%- endfor %}
|
| 78 |
+
{%- if ns.multi_step_tool %}
|
| 79 |
+
{{- raise_exception('No user query found in messages.') }}
|
| 80 |
+
{%- endif %}
|
| 81 |
+
{%- for message in messages %}
|
| 82 |
+
{%- set content = render_content(message.content, true)|trim %}
|
| 83 |
+
{%- if message.role == "system" %}
|
| 84 |
+
{%- if not loop.first %}
|
| 85 |
+
{{- raise_exception('System message must be at the beginning.') }}
|
| 86 |
+
{%- endif %}
|
| 87 |
+
{%- elif message.role == "user" %}
|
| 88 |
+
{{- '<|im_start|>' + message.role + '\n' + content + '<|im_end|>' + '\n' }}
|
| 89 |
+
{%- elif message.role == "assistant" %}
|
| 90 |
+
{%- set reasoning_content = '' %}
|
| 91 |
+
{%- if message.reasoning_content is string %}
|
| 92 |
+
{%- set reasoning_content = message.reasoning_content %}
|
| 93 |
+
{%- else %}
|
| 94 |
+
{%- if '</think>' in content %}
|
| 95 |
+
{%- set reasoning_content = content.split('</think>')[0].rstrip('\n').split('<think>')[-1].lstrip('\n') %}
|
| 96 |
+
{%- set content = content.split('</think>')[-1].lstrip('\n') %}
|
| 97 |
+
{%- endif %}
|
| 98 |
+
{%- endif %}
|
| 99 |
+
{%- set reasoning_content = reasoning_content|trim %}
|
| 100 |
+
{%- if loop.index0 > ns.last_query_index %}
|
| 101 |
+
{{- '<|im_start|>' + message.role + '\n<think>\n' + reasoning_content + '\n</think>\n\n' + content }}
|
| 102 |
+
{%- else %}
|
| 103 |
+
{{- '<|im_start|>' + message.role + '\n' + content }}
|
| 104 |
+
{%- endif %}
|
| 105 |
+
{%- if message.tool_calls and message.tool_calls is iterable and message.tool_calls is not mapping %}
|
| 106 |
+
{%- for tool_call in message.tool_calls %}
|
| 107 |
+
{%- if tool_call.function is defined %}
|
| 108 |
+
{%- set tool_call = tool_call.function %}
|
| 109 |
+
{%- endif %}
|
| 110 |
+
{%- if loop.first %}
|
| 111 |
+
{%- if content|trim %}
|
| 112 |
+
{{- '\n\n<tool_call>\n<function=' + tool_call.name + '>\n' }}
|
| 113 |
+
{%- else %}
|
| 114 |
+
{{- '<tool_call>\n<function=' + tool_call.name + '>\n' }}
|
| 115 |
+
{%- endif %}
|
| 116 |
+
{%- else %}
|
| 117 |
+
{{- '\n<tool_call>\n<function=' + tool_call.name + '>\n' }}
|
| 118 |
+
{%- endif %}
|
| 119 |
+
{%- if tool_call.arguments is defined %}
|
| 120 |
+
{%- for args_name, args_value in tool_call.arguments|items %}
|
| 121 |
+
{{- '<parameter=' + args_name + '>\n' }}
|
| 122 |
+
{%- set args_value = args_value | tojson | safe if args_value is mapping or (args_value is sequence and args_value is not string) else args_value | string %}
|
| 123 |
+
{{- args_value }}
|
| 124 |
+
{{- '\n</parameter>\n' }}
|
| 125 |
+
{%- endfor %}
|
| 126 |
+
{%- endif %}
|
| 127 |
+
{{- '</function>\n</tool_call>' }}
|
| 128 |
+
{%- endfor %}
|
| 129 |
+
{%- endif %}
|
| 130 |
+
{{- '<|im_end|>\n' }}
|
| 131 |
+
{%- elif message.role == "tool" %}
|
| 132 |
+
{%- if loop.previtem and loop.previtem.role != "tool" %}
|
| 133 |
+
{{- '<|im_start|>user' }}
|
| 134 |
+
{%- endif %}
|
| 135 |
+
{{- '\n<tool_response>\n' }}
|
| 136 |
+
{{- content }}
|
| 137 |
+
{{- '\n</tool_response>' }}
|
| 138 |
+
{%- if not loop.last and loop.nextitem.role != "tool" %}
|
| 139 |
+
{{- '<|im_end|>\n' }}
|
| 140 |
+
{%- elif loop.last %}
|
| 141 |
+
{{- '<|im_end|>\n' }}
|
| 142 |
+
{%- endif %}
|
| 143 |
+
{%- else %}
|
| 144 |
+
{{- raise_exception('Unexpected message role.') }}
|
| 145 |
+
{%- endif %}
|
| 146 |
+
{%- endfor %}
|
| 147 |
+
{%- if add_generation_prompt %}
|
| 148 |
+
{{- '<|im_start|>assistant\n' }}
|
| 149 |
+
{%- if enable_thinking is defined and enable_thinking is false %}
|
| 150 |
+
{{- '<think>\n\n</think>\n\n' }}
|
| 151 |
+
{%- else %}
|
| 152 |
+
{{- '<think>\n' }}
|
| 153 |
+
{%- endif %}
|
| 154 |
+
{%- endif %}
|
overgeneralisation_original_Swedish/Qwen3.5-4B-Base_overgeneralisation_splits_original_features_train_overgeneralisation_splits_original_features_test1/checkpoint-1020/tokenizer_config.json
ADDED
|
@@ -0,0 +1,31 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
{
|
| 2 |
+
"add_prefix_space": false,
|
| 3 |
+
"audio_bos_token": "<|audio_start|>",
|
| 4 |
+
"audio_eos_token": "<|audio_end|>",
|
| 5 |
+
"audio_token": "<|audio_pad|>",
|
| 6 |
+
"backend": "tokenizers",
|
| 7 |
+
"bos_token": null,
|
| 8 |
+
"clean_up_tokenization_spaces": false,
|
| 9 |
+
"eos_token": "<|endoftext|>",
|
| 10 |
+
"errors": "replace",
|
| 11 |
+
"image_token": "<|image_pad|>",
|
| 12 |
+
"is_local": false,
|
| 13 |
+
"model_max_length": 262144,
|
| 14 |
+
"model_specific_special_tokens": {
|
| 15 |
+
"audio_bos_token": "<|audio_start|>",
|
| 16 |
+
"audio_eos_token": "<|audio_end|>",
|
| 17 |
+
"audio_token": "<|audio_pad|>",
|
| 18 |
+
"image_token": "<|image_pad|>",
|
| 19 |
+
"video_token": "<|video_pad|>",
|
| 20 |
+
"vision_bos_token": "<|vision_start|>",
|
| 21 |
+
"vision_eos_token": "<|vision_end|>"
|
| 22 |
+
},
|
| 23 |
+
"pad_token": "<|endoftext|>",
|
| 24 |
+
"pretokenize_regex": "(?i:'s|'t|'re|'ve|'m|'ll|'d)|[^\\r\\n\\p{L}\\p{N}]?[\\p{L}\\p{M}]+|\\p{N}| ?[^\\s\\p{L}\\p{M}\\p{N}]+[\\r\\n]*|\\s*[\\r\\n]+|\\s+(?!\\S)|\\s+",
|
| 25 |
+
"split_special_tokens": false,
|
| 26 |
+
"tokenizer_class": "TokenizersBackend",
|
| 27 |
+
"unk_token": null,
|
| 28 |
+
"video_token": "<|video_pad|>",
|
| 29 |
+
"vision_bos_token": "<|vision_start|>",
|
| 30 |
+
"vision_eos_token": "<|vision_end|>"
|
| 31 |
+
}
|
overgeneralisation_original_Swedish/Qwen3.5-4B-Base_overgeneralisation_splits_original_features_train_overgeneralisation_splits_original_features_test1/checkpoint-1020/trainer_state.json
ADDED
|
@@ -0,0 +1,1105 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
{
|
| 2 |
+
"best_global_step": null,
|
| 3 |
+
"best_metric": null,
|
| 4 |
+
"best_model_checkpoint": null,
|
| 5 |
+
"epoch": 2.5379825653798256,
|
| 6 |
+
"eval_steps": 20,
|
| 7 |
+
"global_step": 1020,
|
| 8 |
+
"is_hyper_param_search": false,
|
| 9 |
+
"is_local_process_zero": true,
|
| 10 |
+
"is_world_process_zero": true,
|
| 11 |
+
"log_history": [
|
| 12 |
+
{
|
| 13 |
+
"entropy": 1.9784346982836722,
|
| 14 |
+
"epoch": 0.049813200498132,
|
| 15 |
+
"grad_norm": 3.0229668617248535,
|
| 16 |
+
"learning_rate": 9.526142962415369e-06,
|
| 17 |
+
"loss": 1.7360023498535155,
|
| 18 |
+
"mean_token_accuracy": 0.6449888605624438,
|
| 19 |
+
"num_tokens": 46794.0,
|
| 20 |
+
"step": 20
|
| 21 |
+
},
|
| 22 |
+
{
|
| 23 |
+
"epoch": 0.049813200498132,
|
| 24 |
+
"eval_entropy": 1.41506897571475,
|
| 25 |
+
"eval_loss": 1.1876318454742432,
|
| 26 |
+
"eval_mean_token_accuracy": 0.734131895525511,
|
| 27 |
+
"eval_num_tokens": 46794.0,
|
| 28 |
+
"eval_runtime": 87.8071,
|
| 29 |
+
"eval_samples_per_second": 15.671,
|
| 30 |
+
"eval_steps_per_second": 1.959,
|
| 31 |
+
"step": 20
|
| 32 |
+
},
|
| 33 |
+
{
|
| 34 |
+
"entropy": 1.049924298375845,
|
| 35 |
+
"epoch": 0.099626400996264,
|
| 36 |
+
"grad_norm": 1.5795097351074219,
|
| 37 |
+
"learning_rate": 1.9553661870221022e-05,
|
| 38 |
+
"loss": 0.8944448471069336,
|
| 39 |
+
"mean_token_accuracy": 0.7748479396104813,
|
| 40 |
+
"num_tokens": 90754.0,
|
| 41 |
+
"step": 40
|
| 42 |
+
},
|
| 43 |
+
{
|
| 44 |
+
"epoch": 0.099626400996264,
|
| 45 |
+
"eval_entropy": 0.7996658658565476,
|
| 46 |
+
"eval_loss": 0.7202735543251038,
|
| 47 |
+
"eval_mean_token_accuracy": 0.8070558306089667,
|
| 48 |
+
"eval_num_tokens": 90754.0,
|
| 49 |
+
"eval_runtime": 86.9199,
|
| 50 |
+
"eval_samples_per_second": 15.831,
|
| 51 |
+
"eval_steps_per_second": 1.979,
|
| 52 |
+
"step": 40
|
| 53 |
+
},
|
| 54 |
+
{
|
| 55 |
+
"entropy": 0.7734908878803253,
|
| 56 |
+
"epoch": 0.149439601494396,
|
| 57 |
+
"grad_norm": 1.3136248588562012,
|
| 58 |
+
"learning_rate": 2.9581180778026673e-05,
|
| 59 |
+
"loss": 0.6780608654022217,
|
| 60 |
+
"mean_token_accuracy": 0.8168170280754566,
|
| 61 |
+
"num_tokens": 137472.0,
|
| 62 |
+
"step": 60
|
| 63 |
+
},
|
| 64 |
+
{
|
| 65 |
+
"epoch": 0.149439601494396,
|
| 66 |
+
"eval_entropy": 0.7119324009778888,
|
| 67 |
+
"eval_loss": 0.6554311513900757,
|
| 68 |
+
"eval_mean_token_accuracy": 0.8215604798738346,
|
| 69 |
+
"eval_num_tokens": 137472.0,
|
| 70 |
+
"eval_runtime": 86.8692,
|
| 71 |
+
"eval_samples_per_second": 15.84,
|
| 72 |
+
"eval_steps_per_second": 1.98,
|
| 73 |
+
"step": 60
|
| 74 |
+
},
|
| 75 |
+
{
|
| 76 |
+
"entropy": 0.7071127541363239,
|
| 77 |
+
"epoch": 0.199252801992528,
|
| 78 |
+
"grad_norm": 1.387060284614563,
|
| 79 |
+
"learning_rate": 3.960869968583232e-05,
|
| 80 |
+
"loss": 0.6382100582122803,
|
| 81 |
+
"mean_token_accuracy": 0.8229366384446621,
|
| 82 |
+
"num_tokens": 187408.0,
|
| 83 |
+
"step": 80
|
| 84 |
+
},
|
| 85 |
+
{
|
| 86 |
+
"epoch": 0.199252801992528,
|
| 87 |
+
"eval_entropy": 0.6883931482254073,
|
| 88 |
+
"eval_loss": 0.625065803527832,
|
| 89 |
+
"eval_mean_token_accuracy": 0.828940509710201,
|
| 90 |
+
"eval_num_tokens": 187408.0,
|
| 91 |
+
"eval_runtime": 86.662,
|
| 92 |
+
"eval_samples_per_second": 15.878,
|
| 93 |
+
"eval_steps_per_second": 1.985,
|
| 94 |
+
"step": 80
|
| 95 |
+
},
|
| 96 |
+
{
|
| 97 |
+
"entropy": 0.6800824083387852,
|
| 98 |
+
"epoch": 0.24906600249066002,
|
| 99 |
+
"grad_norm": 0.9892916679382324,
|
| 100 |
+
"learning_rate": 4.963621859363797e-05,
|
| 101 |
+
"loss": 0.6011715888977051,
|
| 102 |
+
"mean_token_accuracy": 0.8323964163661003,
|
| 103 |
+
"num_tokens": 234197.0,
|
| 104 |
+
"step": 100
|
| 105 |
+
},
|
| 106 |
+
{
|
| 107 |
+
"epoch": 0.24906600249066002,
|
| 108 |
+
"eval_entropy": 0.6840810470802839,
|
| 109 |
+
"eval_loss": 0.6037028431892395,
|
| 110 |
+
"eval_mean_token_accuracy": 0.8309669033732525,
|
| 111 |
+
"eval_num_tokens": 234197.0,
|
| 112 |
+
"eval_runtime": 86.4637,
|
| 113 |
+
"eval_samples_per_second": 15.914,
|
| 114 |
+
"eval_steps_per_second": 1.989,
|
| 115 |
+
"step": 100
|
| 116 |
+
},
|
| 117 |
+
{
|
| 118 |
+
"entropy": 0.6776216626167297,
|
| 119 |
+
"epoch": 0.298879202988792,
|
| 120 |
+
"grad_norm": 0.8918434977531433,
|
| 121 |
+
"learning_rate": 5.9663737501443624e-05,
|
| 122 |
+
"loss": 0.5991742610931396,
|
| 123 |
+
"mean_token_accuracy": 0.8300838828086853,
|
| 124 |
+
"num_tokens": 281241.0,
|
| 125 |
+
"step": 120
|
| 126 |
+
},
|
| 127 |
+
{
|
| 128 |
+
"epoch": 0.298879202988792,
|
| 129 |
+
"eval_entropy": 0.690427724705186,
|
| 130 |
+
"eval_loss": 0.5939701795578003,
|
| 131 |
+
"eval_mean_token_accuracy": 0.8345950186945671,
|
| 132 |
+
"eval_num_tokens": 281241.0,
|
| 133 |
+
"eval_runtime": 86.6626,
|
| 134 |
+
"eval_samples_per_second": 15.878,
|
| 135 |
+
"eval_steps_per_second": 1.985,
|
| 136 |
+
"step": 120
|
| 137 |
+
},
|
| 138 |
+
{
|
| 139 |
+
"entropy": 0.6709842771291733,
|
| 140 |
+
"epoch": 0.34869240348692404,
|
| 141 |
+
"grad_norm": 0.9135531187057495,
|
| 142 |
+
"learning_rate": 6.969125640924927e-05,
|
| 143 |
+
"loss": 0.5914147377014161,
|
| 144 |
+
"mean_token_accuracy": 0.8314545609056949,
|
| 145 |
+
"num_tokens": 327393.0,
|
| 146 |
+
"step": 140
|
| 147 |
+
},
|
| 148 |
+
{
|
| 149 |
+
"epoch": 0.34869240348692404,
|
| 150 |
+
"eval_entropy": 0.6584504666023476,
|
| 151 |
+
"eval_loss": 0.5849721431732178,
|
| 152 |
+
"eval_mean_token_accuracy": 0.8357757236375365,
|
| 153 |
+
"eval_num_tokens": 327393.0,
|
| 154 |
+
"eval_runtime": 86.3262,
|
| 155 |
+
"eval_samples_per_second": 15.94,
|
| 156 |
+
"eval_steps_per_second": 1.992,
|
| 157 |
+
"step": 140
|
| 158 |
+
},
|
| 159 |
+
{
|
| 160 |
+
"entropy": 0.6524647936224938,
|
| 161 |
+
"epoch": 0.398505603985056,
|
| 162 |
+
"grad_norm": 0.8651587963104248,
|
| 163 |
+
"learning_rate": 7.971877531705493e-05,
|
| 164 |
+
"loss": 0.5710843563079834,
|
| 165 |
+
"mean_token_accuracy": 0.8396127380430698,
|
| 166 |
+
"num_tokens": 373834.0,
|
| 167 |
+
"step": 160
|
| 168 |
+
},
|
| 169 |
+
{
|
| 170 |
+
"epoch": 0.398505603985056,
|
| 171 |
+
"eval_entropy": 0.6283470298661742,
|
| 172 |
+
"eval_loss": 0.5738973617553711,
|
| 173 |
+
"eval_mean_token_accuracy": 0.8379981181649274,
|
| 174 |
+
"eval_num_tokens": 373834.0,
|
| 175 |
+
"eval_runtime": 86.5619,
|
| 176 |
+
"eval_samples_per_second": 15.896,
|
| 177 |
+
"eval_steps_per_second": 1.987,
|
| 178 |
+
"step": 160
|
| 179 |
+
},
|
| 180 |
+
{
|
| 181 |
+
"entropy": 0.6450445972383022,
|
| 182 |
+
"epoch": 0.44831880448318806,
|
| 183 |
+
"grad_norm": 0.8661723732948303,
|
| 184 |
+
"learning_rate": 8.974629422486058e-05,
|
| 185 |
+
"loss": 0.5677794933319091,
|
| 186 |
+
"mean_token_accuracy": 0.8389350369572639,
|
| 187 |
+
"num_tokens": 422572.0,
|
| 188 |
+
"step": 180
|
| 189 |
+
},
|
| 190 |
+
{
|
| 191 |
+
"epoch": 0.44831880448318806,
|
| 192 |
+
"eval_entropy": 0.6142613257086554,
|
| 193 |
+
"eval_loss": 0.5698265433311462,
|
| 194 |
+
"eval_mean_token_accuracy": 0.8388577273418737,
|
| 195 |
+
"eval_num_tokens": 422572.0,
|
| 196 |
+
"eval_runtime": 86.4443,
|
| 197 |
+
"eval_samples_per_second": 15.918,
|
| 198 |
+
"eval_steps_per_second": 1.99,
|
| 199 |
+
"step": 180
|
| 200 |
+
},
|
| 201 |
+
{
|
| 202 |
+
"entropy": 0.6448334597051144,
|
| 203 |
+
"epoch": 0.49813200498132004,
|
| 204 |
+
"grad_norm": 0.9662242531776428,
|
| 205 |
+
"learning_rate": 9.977381313266624e-05,
|
| 206 |
+
"loss": 0.581433916091919,
|
| 207 |
+
"mean_token_accuracy": 0.8387043006718159,
|
| 208 |
+
"num_tokens": 471879.0,
|
| 209 |
+
"step": 200
|
| 210 |
+
},
|
| 211 |
+
{
|
| 212 |
+
"epoch": 0.49813200498132004,
|
| 213 |
+
"eval_entropy": 0.6154296522916749,
|
| 214 |
+
"eval_loss": 0.5660303831100464,
|
| 215 |
+
"eval_mean_token_accuracy": 0.8412494766850804,
|
| 216 |
+
"eval_num_tokens": 471879.0,
|
| 217 |
+
"eval_runtime": 86.3063,
|
| 218 |
+
"eval_samples_per_second": 15.943,
|
| 219 |
+
"eval_steps_per_second": 1.993,
|
| 220 |
+
"step": 200
|
| 221 |
+
},
|
| 222 |
+
{
|
| 223 |
+
"entropy": 0.6376728117465973,
|
| 224 |
+
"epoch": 0.547945205479452,
|
| 225 |
+
"grad_norm": 0.7618638873100281,
|
| 226 |
+
"learning_rate": 0.00010980133204047189,
|
| 227 |
+
"loss": 0.5678351402282715,
|
| 228 |
+
"mean_token_accuracy": 0.8404546812176704,
|
| 229 |
+
"num_tokens": 520984.0,
|
| 230 |
+
"step": 220
|
| 231 |
+
},
|
| 232 |
+
{
|
| 233 |
+
"epoch": 0.547945205479452,
|
| 234 |
+
"eval_entropy": 0.6181817033956217,
|
| 235 |
+
"eval_loss": 0.5663750171661377,
|
| 236 |
+
"eval_mean_token_accuracy": 0.8388350962899452,
|
| 237 |
+
"eval_num_tokens": 520984.0,
|
| 238 |
+
"eval_runtime": 86.5904,
|
| 239 |
+
"eval_samples_per_second": 15.891,
|
| 240 |
+
"eval_steps_per_second": 1.986,
|
| 241 |
+
"step": 220
|
| 242 |
+
},
|
| 243 |
+
{
|
| 244 |
+
"entropy": 0.6303176879882812,
|
| 245 |
+
"epoch": 0.597758405977584,
|
| 246 |
+
"grad_norm": 0.7571695446968079,
|
| 247 |
+
"learning_rate": 0.00011982885094827753,
|
| 248 |
+
"loss": 0.5502778053283691,
|
| 249 |
+
"mean_token_accuracy": 0.8429657347500324,
|
| 250 |
+
"num_tokens": 566596.0,
|
| 251 |
+
"step": 240
|
| 252 |
+
},
|
| 253 |
+
{
|
| 254 |
+
"epoch": 0.597758405977584,
|
| 255 |
+
"eval_entropy": 0.6252533817707107,
|
| 256 |
+
"eval_loss": 0.5570284128189087,
|
| 257 |
+
"eval_mean_token_accuracy": 0.8427327847064927,
|
| 258 |
+
"eval_num_tokens": 566596.0,
|
| 259 |
+
"eval_runtime": 86.4157,
|
| 260 |
+
"eval_samples_per_second": 15.923,
|
| 261 |
+
"eval_steps_per_second": 1.99,
|
| 262 |
+
"step": 240
|
| 263 |
+
},
|
| 264 |
+
{
|
| 265 |
+
"entropy": 0.6202544964849949,
|
| 266 |
+
"epoch": 0.6475716064757161,
|
| 267 |
+
"grad_norm": 0.6447190642356873,
|
| 268 |
+
"learning_rate": 0.00012985636985608318,
|
| 269 |
+
"loss": 0.5485352993011474,
|
| 270 |
+
"mean_token_accuracy": 0.844165726006031,
|
| 271 |
+
"num_tokens": 613603.0,
|
| 272 |
+
"step": 260
|
| 273 |
+
},
|
| 274 |
+
{
|
| 275 |
+
"epoch": 0.6475716064757161,
|
| 276 |
+
"eval_entropy": 0.6441633552312851,
|
| 277 |
+
"eval_loss": 0.5606644153594971,
|
| 278 |
+
"eval_mean_token_accuracy": 0.842403513054515,
|
| 279 |
+
"eval_num_tokens": 613603.0,
|
| 280 |
+
"eval_runtime": 86.6343,
|
| 281 |
+
"eval_samples_per_second": 15.883,
|
| 282 |
+
"eval_steps_per_second": 1.985,
|
| 283 |
+
"step": 260
|
| 284 |
+
},
|
| 285 |
+
{
|
| 286 |
+
"entropy": 0.6306711677461863,
|
| 287 |
+
"epoch": 0.6973848069738481,
|
| 288 |
+
"grad_norm": 0.7869907021522522,
|
| 289 |
+
"learning_rate": 0.00013988388876388883,
|
| 290 |
+
"loss": 0.5579307556152344,
|
| 291 |
+
"mean_token_accuracy": 0.841247134655714,
|
| 292 |
+
"num_tokens": 658565.0,
|
| 293 |
+
"step": 280
|
| 294 |
+
},
|
| 295 |
+
{
|
| 296 |
+
"epoch": 0.6973848069738481,
|
| 297 |
+
"eval_entropy": 0.6263934678809587,
|
| 298 |
+
"eval_loss": 0.5559113025665283,
|
| 299 |
+
"eval_mean_token_accuracy": 0.8427334743183713,
|
| 300 |
+
"eval_num_tokens": 658565.0,
|
| 301 |
+
"eval_runtime": 86.6403,
|
| 302 |
+
"eval_samples_per_second": 15.882,
|
| 303 |
+
"eval_steps_per_second": 1.985,
|
| 304 |
+
"step": 280
|
| 305 |
+
},
|
| 306 |
+
{
|
| 307 |
+
"entropy": 0.6385872110724449,
|
| 308 |
+
"epoch": 0.7471980074719801,
|
| 309 |
+
"grad_norm": 0.6679229736328125,
|
| 310 |
+
"learning_rate": 0.0001499114076716945,
|
| 311 |
+
"loss": 0.5667279720306396,
|
| 312 |
+
"mean_token_accuracy": 0.8389136254787445,
|
| 313 |
+
"num_tokens": 705680.0,
|
| 314 |
+
"step": 300
|
| 315 |
+
},
|
| 316 |
+
{
|
| 317 |
+
"epoch": 0.7471980074719801,
|
| 318 |
+
"eval_entropy": 0.6141417321077612,
|
| 319 |
+
"eval_loss": 0.5570600628852844,
|
| 320 |
+
"eval_mean_token_accuracy": 0.8437647996253745,
|
| 321 |
+
"eval_num_tokens": 705680.0,
|
| 322 |
+
"eval_runtime": 86.7588,
|
| 323 |
+
"eval_samples_per_second": 15.86,
|
| 324 |
+
"eval_steps_per_second": 1.983,
|
| 325 |
+
"step": 300
|
| 326 |
+
},
|
| 327 |
+
{
|
| 328 |
+
"entropy": 0.6199494235217571,
|
| 329 |
+
"epoch": 0.797011207970112,
|
| 330 |
+
"grad_norm": 0.7924400568008423,
|
| 331 |
+
"learning_rate": 0.00015993892657950015,
|
| 332 |
+
"loss": 0.5529299736022949,
|
| 333 |
+
"mean_token_accuracy": 0.8426973208785057,
|
| 334 |
+
"num_tokens": 752616.0,
|
| 335 |
+
"step": 320
|
| 336 |
+
},
|
| 337 |
+
{
|
| 338 |
+
"epoch": 0.797011207970112,
|
| 339 |
+
"eval_entropy": 0.6133768925833147,
|
| 340 |
+
"eval_loss": 0.556602418422699,
|
| 341 |
+
"eval_mean_token_accuracy": 0.8432947965555413,
|
| 342 |
+
"eval_num_tokens": 752616.0,
|
| 343 |
+
"eval_runtime": 86.492,
|
| 344 |
+
"eval_samples_per_second": 15.909,
|
| 345 |
+
"eval_steps_per_second": 1.989,
|
| 346 |
+
"step": 320
|
| 347 |
+
},
|
| 348 |
+
{
|
| 349 |
+
"entropy": 0.6203986253589392,
|
| 350 |
+
"epoch": 0.8468244084682441,
|
| 351 |
+
"grad_norm": 0.8364354372024536,
|
| 352 |
+
"learning_rate": 0.00016996644548730578,
|
| 353 |
+
"loss": 0.5551144123077393,
|
| 354 |
+
"mean_token_accuracy": 0.8432973213493824,
|
| 355 |
+
"num_tokens": 797151.0,
|
| 356 |
+
"step": 340
|
| 357 |
+
},
|
| 358 |
+
{
|
| 359 |
+
"epoch": 0.8468244084682441,
|
| 360 |
+
"eval_entropy": 0.6017442844634833,
|
| 361 |
+
"eval_loss": 0.5566568374633789,
|
| 362 |
+
"eval_mean_token_accuracy": 0.8437666123689607,
|
| 363 |
+
"eval_num_tokens": 797151.0,
|
| 364 |
+
"eval_runtime": 86.5552,
|
| 365 |
+
"eval_samples_per_second": 15.897,
|
| 366 |
+
"eval_steps_per_second": 1.987,
|
| 367 |
+
"step": 340
|
| 368 |
+
},
|
| 369 |
+
{
|
| 370 |
+
"entropy": 0.6341533534228802,
|
| 371 |
+
"epoch": 0.8966376089663761,
|
| 372 |
+
"grad_norm": 0.7783445715904236,
|
| 373 |
+
"learning_rate": 0.00017999396439511144,
|
| 374 |
+
"loss": 0.5669133186340332,
|
| 375 |
+
"mean_token_accuracy": 0.8379446342587471,
|
| 376 |
+
"num_tokens": 843585.0,
|
| 377 |
+
"step": 360
|
| 378 |
+
},
|
| 379 |
+
{
|
| 380 |
+
"epoch": 0.8966376089663761,
|
| 381 |
+
"eval_entropy": 0.6055107958788095,
|
| 382 |
+
"eval_loss": 0.5599350333213806,
|
| 383 |
+
"eval_mean_token_accuracy": 0.8435030894917112,
|
| 384 |
+
"eval_num_tokens": 843585.0,
|
| 385 |
+
"eval_runtime": 86.4814,
|
| 386 |
+
"eval_samples_per_second": 15.911,
|
| 387 |
+
"eval_steps_per_second": 1.989,
|
| 388 |
+
"step": 360
|
| 389 |
+
},
|
| 390 |
+
{
|
| 391 |
+
"entropy": 0.6306198488920927,
|
| 392 |
+
"epoch": 0.9464508094645081,
|
| 393 |
+
"grad_norm": 0.8449786901473999,
|
| 394 |
+
"learning_rate": 0.0001900214833029171,
|
| 395 |
+
"loss": 0.5739435195922852,
|
| 396 |
+
"mean_token_accuracy": 0.8393832489848136,
|
| 397 |
+
"num_tokens": 889842.0,
|
| 398 |
+
"step": 380
|
| 399 |
+
},
|
| 400 |
+
{
|
| 401 |
+
"epoch": 0.9464508094645081,
|
| 402 |
+
"eval_entropy": 0.6129532439071078,
|
| 403 |
+
"eval_loss": 0.5566295981407166,
|
| 404 |
+
"eval_mean_token_accuracy": 0.8430350880290187,
|
| 405 |
+
"eval_num_tokens": 889842.0,
|
| 406 |
+
"eval_runtime": 86.4643,
|
| 407 |
+
"eval_samples_per_second": 15.914,
|
| 408 |
+
"eval_steps_per_second": 1.989,
|
| 409 |
+
"step": 380
|
| 410 |
+
},
|
| 411 |
+
{
|
| 412 |
+
"entropy": 0.6203123550862074,
|
| 413 |
+
"epoch": 0.9962640099626401,
|
| 414 |
+
"grad_norm": 0.7334314584732056,
|
| 415 |
+
"learning_rate": 0.00020004900221072276,
|
| 416 |
+
"loss": 0.5547565937042236,
|
| 417 |
+
"mean_token_accuracy": 0.8403573960065842,
|
| 418 |
+
"num_tokens": 935589.0,
|
| 419 |
+
"step": 400
|
| 420 |
+
},
|
| 421 |
+
{
|
| 422 |
+
"epoch": 0.9962640099626401,
|
| 423 |
+
"eval_entropy": 0.6275761647279873,
|
| 424 |
+
"eval_loss": 0.5621116757392883,
|
| 425 |
+
"eval_mean_token_accuracy": 0.841587379228237,
|
| 426 |
+
"eval_num_tokens": 935589.0,
|
| 427 |
+
"eval_runtime": 86.4748,
|
| 428 |
+
"eval_samples_per_second": 15.912,
|
| 429 |
+
"eval_steps_per_second": 1.989,
|
| 430 |
+
"step": 400
|
| 431 |
+
},
|
| 432 |
+
{
|
| 433 |
+
"entropy": 0.5795013002860241,
|
| 434 |
+
"epoch": 1.0448318804483188,
|
| 435 |
+
"grad_norm": 0.8858296871185303,
|
| 436 |
+
"learning_rate": 0.0002015421505577756,
|
| 437 |
+
"loss": 0.5183939933776855,
|
| 438 |
+
"mean_token_accuracy": 0.850081592034071,
|
| 439 |
+
"num_tokens": 980589.0,
|
| 440 |
+
"step": 420
|
| 441 |
+
},
|
| 442 |
+
{
|
| 443 |
+
"epoch": 1.0448318804483188,
|
| 444 |
+
"eval_entropy": 0.5583065545489622,
|
| 445 |
+
"eval_loss": 0.5605642199516296,
|
| 446 |
+
"eval_mean_token_accuracy": 0.8439708411000496,
|
| 447 |
+
"eval_num_tokens": 980589.0,
|
| 448 |
+
"eval_runtime": 86.5422,
|
| 449 |
+
"eval_samples_per_second": 15.9,
|
| 450 |
+
"eval_steps_per_second": 1.987,
|
| 451 |
+
"step": 420
|
| 452 |
+
},
|
| 453 |
+
{
|
| 454 |
+
"entropy": 0.5671238023787737,
|
| 455 |
+
"epoch": 1.0946450809464507,
|
| 456 |
+
"grad_norm": 0.6882498264312744,
|
| 457 |
+
"learning_rate": 0.00020150112347025443,
|
| 458 |
+
"loss": 0.5077326774597168,
|
| 459 |
+
"mean_token_accuracy": 0.8489868573844432,
|
| 460 |
+
"num_tokens": 1027852.0,
|
| 461 |
+
"step": 440
|
| 462 |
+
},
|
| 463 |
+
{
|
| 464 |
+
"epoch": 1.0946450809464507,
|
| 465 |
+
"eval_entropy": 0.5868900277933409,
|
| 466 |
+
"eval_loss": 0.5602695345878601,
|
| 467 |
+
"eval_mean_token_accuracy": 0.8428842161977014,
|
| 468 |
+
"eval_num_tokens": 1027852.0,
|
| 469 |
+
"eval_runtime": 86.623,
|
| 470 |
+
"eval_samples_per_second": 15.885,
|
| 471 |
+
"eval_steps_per_second": 1.986,
|
| 472 |
+
"step": 440
|
| 473 |
+
},
|
| 474 |
+
{
|
| 475 |
+
"entropy": 0.5533561781048775,
|
| 476 |
+
"epoch": 1.1444582814445827,
|
| 477 |
+
"grad_norm": 0.7717723250389099,
|
| 478 |
+
"learning_rate": 0.0002014297192297181,
|
| 479 |
+
"loss": 0.4954517364501953,
|
| 480 |
+
"mean_token_accuracy": 0.8529035650193691,
|
| 481 |
+
"num_tokens": 1077649.0,
|
| 482 |
+
"step": 460
|
| 483 |
+
},
|
| 484 |
+
{
|
| 485 |
+
"epoch": 1.1444582814445827,
|
| 486 |
+
"eval_entropy": 0.5600803743961246,
|
| 487 |
+
"eval_loss": 0.5608077645301819,
|
| 488 |
+
"eval_mean_token_accuracy": 0.8445036771685578,
|
| 489 |
+
"eval_num_tokens": 1077649.0,
|
| 490 |
+
"eval_runtime": 86.1316,
|
| 491 |
+
"eval_samples_per_second": 15.976,
|
| 492 |
+
"eval_steps_per_second": 1.997,
|
| 493 |
+
"step": 460
|
| 494 |
+
},
|
| 495 |
+
{
|
| 496 |
+
"entropy": 0.5692154694348573,
|
| 497 |
+
"epoch": 1.1942714819427147,
|
| 498 |
+
"grad_norm": 0.7322827577590942,
|
| 499 |
+
"learning_rate": 0.0002013279593707117,
|
| 500 |
+
"loss": 0.505049467086792,
|
| 501 |
+
"mean_token_accuracy": 0.8551576808094978,
|
| 502 |
+
"num_tokens": 1124872.0,
|
| 503 |
+
"step": 480
|
| 504 |
+
},
|
| 505 |
+
{
|
| 506 |
+
"epoch": 1.1942714819427147,
|
| 507 |
+
"eval_entropy": 0.5732695829383162,
|
| 508 |
+
"eval_loss": 0.5594323873519897,
|
| 509 |
+
"eval_mean_token_accuracy": 0.8449713407560836,
|
| 510 |
+
"eval_num_tokens": 1124872.0,
|
| 511 |
+
"eval_runtime": 86.2726,
|
| 512 |
+
"eval_samples_per_second": 15.949,
|
| 513 |
+
"eval_steps_per_second": 1.994,
|
| 514 |
+
"step": 480
|
| 515 |
+
},
|
| 516 |
+
{
|
| 517 |
+
"entropy": 0.5817618492990733,
|
| 518 |
+
"epoch": 1.244084682440847,
|
| 519 |
+
"grad_norm": 1.1776764392852783,
|
| 520 |
+
"learning_rate": 0.0002011958745826208,
|
| 521 |
+
"loss": 0.5137609958648681,
|
| 522 |
+
"mean_token_accuracy": 0.8521522544324398,
|
| 523 |
+
"num_tokens": 1168698.0,
|
| 524 |
+
"step": 500
|
| 525 |
+
},
|
| 526 |
+
{
|
| 527 |
+
"epoch": 1.244084682440847,
|
| 528 |
+
"eval_entropy": 0.5662581343636957,
|
| 529 |
+
"eval_loss": 0.5595026016235352,
|
| 530 |
+
"eval_mean_token_accuracy": 0.8441977164773053,
|
| 531 |
+
"eval_num_tokens": 1168698.0,
|
| 532 |
+
"eval_runtime": 86.7261,
|
| 533 |
+
"eval_samples_per_second": 15.866,
|
| 534 |
+
"eval_steps_per_second": 1.983,
|
| 535 |
+
"step": 500
|
| 536 |
+
},
|
| 537 |
+
{
|
| 538 |
+
"entropy": 0.5712925456464291,
|
| 539 |
+
"epoch": 1.293897882938979,
|
| 540 |
+
"grad_norm": 0.7960361838340759,
|
| 541 |
+
"learning_rate": 0.0002010335047004159,
|
| 542 |
+
"loss": 0.5134767532348633,
|
| 543 |
+
"mean_token_accuracy": 0.8513577707111836,
|
| 544 |
+
"num_tokens": 1216679.0,
|
| 545 |
+
"step": 520
|
| 546 |
+
},
|
| 547 |
+
{
|
| 548 |
+
"epoch": 1.293897882938979,
|
| 549 |
+
"eval_entropy": 0.5441222797299541,
|
| 550 |
+
"eval_loss": 0.5535460114479065,
|
| 551 |
+
"eval_mean_token_accuracy": 0.8450886118550633,
|
| 552 |
+
"eval_num_tokens": 1216679.0,
|
| 553 |
+
"eval_runtime": 86.2675,
|
| 554 |
+
"eval_samples_per_second": 15.95,
|
| 555 |
+
"eval_steps_per_second": 1.994,
|
| 556 |
+
"step": 520
|
| 557 |
+
},
|
| 558 |
+
{
|
| 559 |
+
"entropy": 0.5787045754492283,
|
| 560 |
+
"epoch": 1.3437110834371109,
|
| 561 |
+
"grad_norm": 0.9205410480499268,
|
| 562 |
+
"learning_rate": 0.00020084089869263887,
|
| 563 |
+
"loss": 0.5119701862335205,
|
| 564 |
+
"mean_token_accuracy": 0.8503516331315041,
|
| 565 |
+
"num_tokens": 1261365.0,
|
| 566 |
+
"step": 540
|
| 567 |
+
},
|
| 568 |
+
{
|
| 569 |
+
"epoch": 1.3437110834371109,
|
| 570 |
+
"eval_entropy": 0.5744457827057949,
|
| 571 |
+
"eval_loss": 0.5514978766441345,
|
| 572 |
+
"eval_mean_token_accuracy": 0.845929987901865,
|
| 573 |
+
"eval_num_tokens": 1261365.0,
|
| 574 |
+
"eval_runtime": 86.2299,
|
| 575 |
+
"eval_samples_per_second": 15.957,
|
| 576 |
+
"eval_steps_per_second": 1.995,
|
| 577 |
+
"step": 540
|
| 578 |
+
},
|
| 579 |
+
{
|
| 580 |
+
"entropy": 0.5739392962306737,
|
| 581 |
+
"epoch": 1.3935242839352429,
|
| 582 |
+
"grad_norm": 0.7475653886795044,
|
| 583 |
+
"learning_rate": 0.00020061811464663464,
|
| 584 |
+
"loss": 0.5189042091369629,
|
| 585 |
+
"mean_token_accuracy": 0.8492388024926185,
|
| 586 |
+
"num_tokens": 1306879.0,
|
| 587 |
+
"step": 560
|
| 588 |
+
},
|
| 589 |
+
{
|
| 590 |
+
"epoch": 1.3935242839352429,
|
| 591 |
+
"eval_entropy": 0.6116398271433142,
|
| 592 |
+
"eval_loss": 0.551732063293457,
|
| 593 |
+
"eval_mean_token_accuracy": 0.8450756967067719,
|
| 594 |
+
"eval_num_tokens": 1306879.0,
|
| 595 |
+
"eval_runtime": 86.6081,
|
| 596 |
+
"eval_samples_per_second": 15.888,
|
| 597 |
+
"eval_steps_per_second": 1.986,
|
| 598 |
+
"step": 560
|
| 599 |
+
},
|
| 600 |
+
{
|
| 601 |
+
"entropy": 0.5755622573196888,
|
| 602 |
+
"epoch": 1.4433374844333748,
|
| 603 |
+
"grad_norm": 0.8218411803245544,
|
| 604 |
+
"learning_rate": 0.00020036521975103286,
|
| 605 |
+
"loss": 0.5106248378753662,
|
| 606 |
+
"mean_token_accuracy": 0.8506785586476326,
|
| 607 |
+
"num_tokens": 1353534.0,
|
| 608 |
+
"step": 580
|
| 609 |
+
},
|
| 610 |
+
{
|
| 611 |
+
"epoch": 1.4433374844333748,
|
| 612 |
+
"eval_entropy": 0.5906928708386976,
|
| 613 |
+
"eval_loss": 0.551278829574585,
|
| 614 |
+
"eval_mean_token_accuracy": 0.8462819308042526,
|
| 615 |
+
"eval_num_tokens": 1353534.0,
|
| 616 |
+
"eval_runtime": 86.5438,
|
| 617 |
+
"eval_samples_per_second": 15.899,
|
| 618 |
+
"eval_steps_per_second": 1.987,
|
| 619 |
+
"step": 580
|
| 620 |
+
},
|
| 621 |
+
{
|
| 622 |
+
"entropy": 0.5694822132587433,
|
| 623 |
+
"epoch": 1.4931506849315068,
|
| 624 |
+
"grad_norm": 0.8880652189254761,
|
| 625 |
+
"learning_rate": 0.00020008229027548475,
|
| 626 |
+
"loss": 0.5140334606170655,
|
| 627 |
+
"mean_token_accuracy": 0.8521522797644139,
|
| 628 |
+
"num_tokens": 1399537.0,
|
| 629 |
+
"step": 600
|
| 630 |
+
},
|
| 631 |
+
{
|
| 632 |
+
"epoch": 1.4931506849315068,
|
| 633 |
+
"eval_entropy": 0.5599641964532608,
|
| 634 |
+
"eval_loss": 0.5501875877380371,
|
| 635 |
+
"eval_mean_token_accuracy": 0.8467660788879838,
|
| 636 |
+
"eval_num_tokens": 1399537.0,
|
| 637 |
+
"eval_runtime": 86.6458,
|
| 638 |
+
"eval_samples_per_second": 15.881,
|
| 639 |
+
"eval_steps_per_second": 1.985,
|
| 640 |
+
"step": 600
|
| 641 |
+
},
|
| 642 |
+
{
|
| 643 |
+
"entropy": 0.5675108034163714,
|
| 644 |
+
"epoch": 1.5429638854296388,
|
| 645 |
+
"grad_norm": 0.837087094783783,
|
| 646 |
+
"learning_rate": 0.0001997694115476612,
|
| 647 |
+
"loss": 0.5099846363067627,
|
| 648 |
+
"mean_token_accuracy": 0.8543680295348167,
|
| 649 |
+
"num_tokens": 1448422.0,
|
| 650 |
+
"step": 620
|
| 651 |
+
},
|
| 652 |
+
{
|
| 653 |
+
"epoch": 1.5429638854296388,
|
| 654 |
+
"eval_entropy": 0.5728072581249614,
|
| 655 |
+
"eval_loss": 0.5445425510406494,
|
| 656 |
+
"eval_mean_token_accuracy": 0.8474342175001321,
|
| 657 |
+
"eval_num_tokens": 1448422.0,
|
| 658 |
+
"eval_runtime": 86.4859,
|
| 659 |
+
"eval_samples_per_second": 15.91,
|
| 660 |
+
"eval_steps_per_second": 1.989,
|
| 661 |
+
"step": 620
|
| 662 |
+
},
|
| 663 |
+
{
|
| 664 |
+
"entropy": 0.5700885068625212,
|
| 665 |
+
"epoch": 1.592777085927771,
|
| 666 |
+
"grad_norm": 0.6598765850067139,
|
| 667 |
+
"learning_rate": 0.000199426677927519,
|
| 668 |
+
"loss": 0.5122694969177246,
|
| 669 |
+
"mean_token_accuracy": 0.8519927568733692,
|
| 670 |
+
"num_tokens": 1495009.0,
|
| 671 |
+
"step": 640
|
| 672 |
+
},
|
| 673 |
+
{
|
| 674 |
+
"epoch": 1.592777085927771,
|
| 675 |
+
"eval_entropy": 0.5476993622128353,
|
| 676 |
+
"eval_loss": 0.5427973866462708,
|
| 677 |
+
"eval_mean_token_accuracy": 0.8478512147138285,
|
| 678 |
+
"eval_num_tokens": 1495009.0,
|
| 679 |
+
"eval_runtime": 86.4172,
|
| 680 |
+
"eval_samples_per_second": 15.923,
|
| 681 |
+
"eval_steps_per_second": 1.99,
|
| 682 |
+
"step": 640
|
| 683 |
+
},
|
| 684 |
+
{
|
| 685 |
+
"entropy": 0.5829229176044464,
|
| 686 |
+
"epoch": 1.6425902864259028,
|
| 687 |
+
"grad_norm": 0.6965194940567017,
|
| 688 |
+
"learning_rate": 0.00019905419277884342,
|
| 689 |
+
"loss": 0.5253659725189209,
|
| 690 |
+
"mean_token_accuracy": 0.8493309423327446,
|
| 691 |
+
"num_tokens": 1536932.0,
|
| 692 |
+
"step": 660
|
| 693 |
+
},
|
| 694 |
+
{
|
| 695 |
+
"epoch": 1.6425902864259028,
|
| 696 |
+
"eval_entropy": 0.5666290084983028,
|
| 697 |
+
"eval_loss": 0.5467478036880493,
|
| 698 |
+
"eval_mean_token_accuracy": 0.8479407703460649,
|
| 699 |
+
"eval_num_tokens": 1536932.0,
|
| 700 |
+
"eval_runtime": 86.4414,
|
| 701 |
+
"eval_samples_per_second": 15.918,
|
| 702 |
+
"eval_steps_per_second": 1.99,
|
| 703 |
+
"step": 660
|
| 704 |
+
},
|
| 705 |
+
{
|
| 706 |
+
"entropy": 0.5498311135917902,
|
| 707 |
+
"epoch": 1.692403486924035,
|
| 708 |
+
"grad_norm": 0.636583685874939,
|
| 709 |
+
"learning_rate": 0.00019865206843807482,
|
| 710 |
+
"loss": 0.49981012344360354,
|
| 711 |
+
"mean_token_accuracy": 0.8560848504304885,
|
| 712 |
+
"num_tokens": 1585718.0,
|
| 713 |
+
"step": 680
|
| 714 |
+
},
|
| 715 |
+
{
|
| 716 |
+
"epoch": 1.692403486924035,
|
| 717 |
+
"eval_entropy": 0.539117265406043,
|
| 718 |
+
"eval_loss": 0.53994220495224,
|
| 719 |
+
"eval_mean_token_accuracy": 0.8488582601380903,
|
| 720 |
+
"eval_num_tokens": 1585718.0,
|
| 721 |
+
"eval_runtime": 86.5296,
|
| 722 |
+
"eval_samples_per_second": 15.902,
|
| 723 |
+
"eval_steps_per_second": 1.988,
|
| 724 |
+
"step": 680
|
| 725 |
+
},
|
| 726 |
+
{
|
| 727 |
+
"entropy": 0.5543891470879316,
|
| 728 |
+
"epoch": 1.7422166874221667,
|
| 729 |
+
"grad_norm": 0.6068442463874817,
|
| 730 |
+
"learning_rate": 0.0001982204261804297,
|
| 731 |
+
"loss": 0.498047399520874,
|
| 732 |
+
"mean_token_accuracy": 0.8554679051041603,
|
| 733 |
+
"num_tokens": 1635718.0,
|
| 734 |
+
"step": 700
|
| 735 |
+
},
|
| 736 |
+
{
|
| 737 |
+
"epoch": 1.7422166874221667,
|
| 738 |
+
"eval_entropy": 0.5703774151760478,
|
| 739 |
+
"eval_loss": 0.5300245881080627,
|
| 740 |
+
"eval_mean_token_accuracy": 0.850798153946566,
|
| 741 |
+
"eval_num_tokens": 1635718.0,
|
| 742 |
+
"eval_runtime": 86.6456,
|
| 743 |
+
"eval_samples_per_second": 15.881,
|
| 744 |
+
"eval_steps_per_second": 1.985,
|
| 745 |
+
"step": 700
|
| 746 |
+
},
|
| 747 |
+
{
|
| 748 |
+
"entropy": 0.546524541825056,
|
| 749 |
+
"epoch": 1.792029887920299,
|
| 750 |
+
"grad_norm": 0.7274155020713806,
|
| 751 |
+
"learning_rate": 0.00019775939618332566,
|
| 752 |
+
"loss": 0.4988589286804199,
|
| 753 |
+
"mean_token_accuracy": 0.853422473371029,
|
| 754 |
+
"num_tokens": 1681291.0,
|
| 755 |
+
"step": 720
|
| 756 |
+
},
|
| 757 |
+
{
|
| 758 |
+
"epoch": 1.792029887920299,
|
| 759 |
+
"eval_entropy": 0.5614905688305234,
|
| 760 |
+
"eval_loss": 0.5350332260131836,
|
| 761 |
+
"eval_mean_token_accuracy": 0.8492204359797544,
|
| 762 |
+
"eval_num_tokens": 1681291.0,
|
| 763 |
+
"eval_runtime": 86.7581,
|
| 764 |
+
"eval_samples_per_second": 15.86,
|
| 765 |
+
"eval_steps_per_second": 1.983,
|
| 766 |
+
"step": 720
|
| 767 |
+
},
|
| 768 |
+
{
|
| 769 |
+
"entropy": 0.5519792139530182,
|
| 770 |
+
"epoch": 1.841843088418431,
|
| 771 |
+
"grad_norm": 0.663466215133667,
|
| 772 |
+
"learning_rate": 0.00019726911748712167,
|
| 773 |
+
"loss": 0.5099314212799072,
|
| 774 |
+
"mean_token_accuracy": 0.848412600159645,
|
| 775 |
+
"num_tokens": 1729102.0,
|
| 776 |
+
"step": 740
|
| 777 |
+
},
|
| 778 |
+
{
|
| 779 |
+
"epoch": 1.841843088418431,
|
| 780 |
+
"eval_entropy": 0.5583519090053647,
|
| 781 |
+
"eval_loss": 0.530483603477478,
|
| 782 |
+
"eval_mean_token_accuracy": 0.8500003374593202,
|
| 783 |
+
"eval_num_tokens": 1729102.0,
|
| 784 |
+
"eval_runtime": 86.3961,
|
| 785 |
+
"eval_samples_per_second": 15.927,
|
| 786 |
+
"eval_steps_per_second": 1.991,
|
| 787 |
+
"step": 740
|
| 788 |
+
},
|
| 789 |
+
{
|
| 790 |
+
"entropy": 0.5454779766499996,
|
| 791 |
+
"epoch": 1.891656288916563,
|
| 792 |
+
"grad_norm": 0.890394926071167,
|
| 793 |
+
"learning_rate": 0.00019674973795318548,
|
| 794 |
+
"loss": 0.4931994915008545,
|
| 795 |
+
"mean_token_accuracy": 0.8540832489728928,
|
| 796 |
+
"num_tokens": 1773578.0,
|
| 797 |
+
"step": 760
|
| 798 |
+
},
|
| 799 |
+
{
|
| 800 |
+
"epoch": 1.891656288916563,
|
| 801 |
+
"eval_entropy": 0.572755502406941,
|
| 802 |
+
"eval_loss": 0.5415747761726379,
|
| 803 |
+
"eval_mean_token_accuracy": 0.8444425803284312,
|
| 804 |
+
"eval_num_tokens": 1773578.0,
|
| 805 |
+
"eval_runtime": 86.4323,
|
| 806 |
+
"eval_samples_per_second": 15.92,
|
| 807 |
+
"eval_steps_per_second": 1.99,
|
| 808 |
+
"step": 760
|
| 809 |
+
},
|
| 810 |
+
{
|
| 811 |
+
"entropy": 0.5392089951783419,
|
| 812 |
+
"epoch": 1.9414694894146949,
|
| 813 |
+
"grad_norm": 0.632411777973175,
|
| 814 |
+
"learning_rate": 0.00019620141421930058,
|
| 815 |
+
"loss": 0.4957888603210449,
|
| 816 |
+
"mean_token_accuracy": 0.8549866065382957,
|
| 817 |
+
"num_tokens": 1821725.0,
|
| 818 |
+
"step": 780
|
| 819 |
+
},
|
| 820 |
+
{
|
| 821 |
+
"epoch": 1.9414694894146949,
|
| 822 |
+
"eval_entropy": 0.540764772961306,
|
| 823 |
+
"eval_loss": 0.5327216386795044,
|
| 824 |
+
"eval_mean_token_accuracy": 0.850631088364956,
|
| 825 |
+
"eval_num_tokens": 1821725.0,
|
| 826 |
+
"eval_runtime": 86.8097,
|
| 827 |
+
"eval_samples_per_second": 15.851,
|
| 828 |
+
"eval_steps_per_second": 1.981,
|
| 829 |
+
"step": 780
|
| 830 |
+
},
|
| 831 |
+
{
|
| 832 |
+
"entropy": 0.5674678739160299,
|
| 833 |
+
"epoch": 1.9912826899128269,
|
| 834 |
+
"grad_norm": 0.6958843469619751,
|
| 835 |
+
"learning_rate": 0.0001956243116524263,
|
| 836 |
+
"loss": 0.504389762878418,
|
| 837 |
+
"mean_token_accuracy": 0.8527948908507824,
|
| 838 |
+
"num_tokens": 1868431.0,
|
| 839 |
+
"step": 800
|
| 840 |
+
},
|
| 841 |
+
{
|
| 842 |
+
"epoch": 1.9912826899128269,
|
| 843 |
+
"eval_entropy": 0.530262403190136,
|
| 844 |
+
"eval_loss": 0.5308871865272522,
|
| 845 |
+
"eval_mean_token_accuracy": 0.8522498046242913,
|
| 846 |
+
"eval_num_tokens": 1868431.0,
|
| 847 |
+
"eval_runtime": 86.7942,
|
| 848 |
+
"eval_samples_per_second": 15.854,
|
| 849 |
+
"eval_steps_per_second": 1.982,
|
| 850 |
+
"step": 800
|
| 851 |
+
},
|
| 852 |
+
{
|
| 853 |
+
"entropy": 0.4742849511213792,
|
| 854 |
+
"epoch": 2.0398505603985058,
|
| 855 |
+
"grad_norm": 0.6941492557525635,
|
| 856 |
+
"learning_rate": 0.00019501860429882556,
|
| 857 |
+
"loss": 0.418599271774292,
|
| 858 |
+
"mean_token_accuracy": 0.8748210859604371,
|
| 859 |
+
"num_tokens": 1915280.0,
|
| 860 |
+
"step": 820
|
| 861 |
+
},
|
| 862 |
+
{
|
| 863 |
+
"epoch": 2.0398505603985058,
|
| 864 |
+
"eval_entropy": 0.504602165069691,
|
| 865 |
+
"eval_loss": 0.542878270149231,
|
| 866 |
+
"eval_mean_token_accuracy": 0.8507604484641275,
|
| 867 |
+
"eval_num_tokens": 1915280.0,
|
| 868 |
+
"eval_runtime": 86.7841,
|
| 869 |
+
"eval_samples_per_second": 15.855,
|
| 870 |
+
"eval_steps_per_second": 1.982,
|
| 871 |
+
"step": 820
|
| 872 |
+
},
|
| 873 |
+
{
|
| 874 |
+
"entropy": 0.45857742577791216,
|
| 875 |
+
"epoch": 2.0896637608966375,
|
| 876 |
+
"grad_norm": 0.5791997909545898,
|
| 877 |
+
"learning_rate": 0.00019438447483157478,
|
| 878 |
+
"loss": 0.399777889251709,
|
| 879 |
+
"mean_token_accuracy": 0.8754058346152306,
|
| 880 |
+
"num_tokens": 1965306.0,
|
| 881 |
+
"step": 840
|
| 882 |
+
},
|
| 883 |
+
{
|
| 884 |
+
"epoch": 2.0896637608966375,
|
| 885 |
+
"eval_entropy": 0.5028848362176918,
|
| 886 |
+
"eval_loss": 0.5356478095054626,
|
| 887 |
+
"eval_mean_token_accuracy": 0.8525635412959165,
|
| 888 |
+
"eval_num_tokens": 1965306.0,
|
| 889 |
+
"eval_runtime": 86.6707,
|
| 890 |
+
"eval_samples_per_second": 15.876,
|
| 891 |
+
"eval_steps_per_second": 1.985,
|
| 892 |
+
"step": 840
|
| 893 |
+
},
|
| 894 |
+
{
|
| 895 |
+
"entropy": 0.4869446292519569,
|
| 896 |
+
"epoch": 2.1394769613947697,
|
| 897 |
+
"grad_norm": 0.6483516693115234,
|
| 898 |
+
"learning_rate": 0.00019372211449547223,
|
| 899 |
+
"loss": 0.40715818405151366,
|
| 900 |
+
"mean_token_accuracy": 0.875113020837307,
|
| 901 |
+
"num_tokens": 2008562.0,
|
| 902 |
+
"step": 860
|
| 903 |
+
},
|
| 904 |
+
{
|
| 905 |
+
"epoch": 2.1394769613947697,
|
| 906 |
+
"eval_entropy": 0.4928991326759028,
|
| 907 |
+
"eval_loss": 0.5419561862945557,
|
| 908 |
+
"eval_mean_token_accuracy": 0.8516040146350861,
|
| 909 |
+
"eval_num_tokens": 2008562.0,
|
| 910 |
+
"eval_runtime": 87.0686,
|
| 911 |
+
"eval_samples_per_second": 15.804,
|
| 912 |
+
"eval_steps_per_second": 1.975,
|
| 913 |
+
"step": 860
|
| 914 |
+
},
|
| 915 |
+
{
|
| 916 |
+
"entropy": 0.45819590501487256,
|
| 917 |
+
"epoch": 2.1892901618929015,
|
| 918 |
+
"grad_norm": 0.6661920547485352,
|
| 919 |
+
"learning_rate": 0.00019303172304936108,
|
| 920 |
+
"loss": 0.39511430263519287,
|
| 921 |
+
"mean_token_accuracy": 0.8780680045485496,
|
| 922 |
+
"num_tokens": 2056474.0,
|
| 923 |
+
"step": 880
|
| 924 |
+
},
|
| 925 |
+
{
|
| 926 |
+
"epoch": 2.1892901618929015,
|
| 927 |
+
"eval_entropy": 0.48602560647698334,
|
| 928 |
+
"eval_loss": 0.5436084866523743,
|
| 929 |
+
"eval_mean_token_accuracy": 0.8500938470973525,
|
| 930 |
+
"eval_num_tokens": 2056474.0,
|
| 931 |
+
"eval_runtime": 86.6809,
|
| 932 |
+
"eval_samples_per_second": 15.874,
|
| 933 |
+
"eval_steps_per_second": 1.984,
|
| 934 |
+
"step": 880
|
| 935 |
+
},
|
| 936 |
+
{
|
| 937 |
+
"entropy": 0.4780638810247183,
|
| 938 |
+
"epoch": 2.2391033623910337,
|
| 939 |
+
"grad_norm": 0.6870484352111816,
|
| 940 |
+
"learning_rate": 0.0001923135087058851,
|
| 941 |
+
"loss": 0.4061615467071533,
|
| 942 |
+
"mean_token_accuracy": 0.8766494184732437,
|
| 943 |
+
"num_tokens": 2103543.0,
|
| 944 |
+
"step": 900
|
| 945 |
+
},
|
| 946 |
+
{
|
| 947 |
+
"epoch": 2.2391033623910337,
|
| 948 |
+
"eval_entropy": 0.48236206035281337,
|
| 949 |
+
"eval_loss": 0.5446090698242188,
|
| 950 |
+
"eval_mean_token_accuracy": 0.8507725513258646,
|
| 951 |
+
"eval_num_tokens": 2103543.0,
|
| 952 |
+
"eval_runtime": 86.7398,
|
| 953 |
+
"eval_samples_per_second": 15.864,
|
| 954 |
+
"eval_steps_per_second": 1.983,
|
| 955 |
+
"step": 900
|
| 956 |
+
},
|
| 957 |
+
{
|
| 958 |
+
"entropy": 0.463029869645834,
|
| 959 |
+
"epoch": 2.2889165628891655,
|
| 960 |
+
"grad_norm": 0.6894590854644775,
|
| 961 |
+
"learning_rate": 0.00019156768806869427,
|
| 962 |
+
"loss": 0.39602413177490237,
|
| 963 |
+
"mean_token_accuracy": 0.876420046389103,
|
| 964 |
+
"num_tokens": 2147861.0,
|
| 965 |
+
"step": 920
|
| 966 |
+
},
|
| 967 |
+
{
|
| 968 |
+
"epoch": 2.2889165628891655,
|
| 969 |
+
"eval_entropy": 0.4904779093556626,
|
| 970 |
+
"eval_loss": 0.5404934287071228,
|
| 971 |
+
"eval_mean_token_accuracy": 0.852238280828609,
|
| 972 |
+
"eval_num_tokens": 2147861.0,
|
| 973 |
+
"eval_runtime": 86.5348,
|
| 974 |
+
"eval_samples_per_second": 15.901,
|
| 975 |
+
"eval_steps_per_second": 1.988,
|
| 976 |
+
"step": 920
|
| 977 |
+
},
|
| 978 |
+
{
|
| 979 |
+
"entropy": 0.4817025110125542,
|
| 980 |
+
"epoch": 2.3387297633872977,
|
| 981 |
+
"grad_norm": 0.7756227254867554,
|
| 982 |
+
"learning_rate": 0.00019079448606712033,
|
| 983 |
+
"loss": 0.4177968502044678,
|
| 984 |
+
"mean_token_accuracy": 0.8712256088852882,
|
| 985 |
+
"num_tokens": 2190561.0,
|
| 986 |
+
"step": 940
|
| 987 |
+
},
|
| 988 |
+
{
|
| 989 |
+
"epoch": 2.3387297633872977,
|
| 990 |
+
"eval_entropy": 0.5153802815218305,
|
| 991 |
+
"eval_loss": 0.5424937605857849,
|
| 992 |
+
"eval_mean_token_accuracy": 0.8506565759348315,
|
| 993 |
+
"eval_num_tokens": 2190561.0,
|
| 994 |
+
"eval_runtime": 86.8973,
|
| 995 |
+
"eval_samples_per_second": 15.835,
|
| 996 |
+
"eval_steps_per_second": 1.979,
|
| 997 |
+
"step": 940
|
| 998 |
+
},
|
| 999 |
+
{
|
| 1000 |
+
"entropy": 0.46456389091908934,
|
| 1001 |
+
"epoch": 2.3885429638854294,
|
| 1002 |
+
"grad_norm": 1.2000319957733154,
|
| 1003 |
+
"learning_rate": 0.00018999413588834105,
|
| 1004 |
+
"loss": 0.4084665775299072,
|
| 1005 |
+
"mean_token_accuracy": 0.8750658087432385,
|
| 1006 |
+
"num_tokens": 2239412.0,
|
| 1007 |
+
"step": 960
|
| 1008 |
+
},
|
| 1009 |
+
{
|
| 1010 |
+
"epoch": 2.3885429638854294,
|
| 1011 |
+
"eval_entropy": 0.4849439303195754,
|
| 1012 |
+
"eval_loss": 0.545662522315979,
|
| 1013 |
+
"eval_mean_token_accuracy": 0.8491013112456299,
|
| 1014 |
+
"eval_num_tokens": 2239412.0,
|
| 1015 |
+
"eval_runtime": 86.9049,
|
| 1016 |
+
"eval_samples_per_second": 15.833,
|
| 1017 |
+
"eval_steps_per_second": 1.979,
|
| 1018 |
+
"step": 960
|
| 1019 |
+
},
|
| 1020 |
+
{
|
| 1021 |
+
"entropy": 0.4857471022754908,
|
| 1022 |
+
"epoch": 2.4383561643835616,
|
| 1023 |
+
"grad_norm": 0.9696341753005981,
|
| 1024 |
+
"learning_rate": 0.0001891668789070541,
|
| 1025 |
+
"loss": 0.4149796962738037,
|
| 1026 |
+
"mean_token_accuracy": 0.8704176343977451,
|
| 1027 |
+
"num_tokens": 2286283.0,
|
| 1028 |
+
"step": 980
|
| 1029 |
+
},
|
| 1030 |
+
{
|
| 1031 |
+
"epoch": 2.4383561643835616,
|
| 1032 |
+
"eval_entropy": 0.4872790058684904,
|
| 1033 |
+
"eval_loss": 0.5412707924842834,
|
| 1034 |
+
"eval_mean_token_accuracy": 0.8509329602468846,
|
| 1035 |
+
"eval_num_tokens": 2286283.0,
|
| 1036 |
+
"eval_runtime": 86.7846,
|
| 1037 |
+
"eval_samples_per_second": 15.855,
|
| 1038 |
+
"eval_steps_per_second": 1.982,
|
| 1039 |
+
"step": 980
|
| 1040 |
+
},
|
| 1041 |
+
{
|
| 1042 |
+
"entropy": 0.4727417893707752,
|
| 1043 |
+
"epoch": 2.488169364881694,
|
| 1044 |
+
"grad_norm": 0.7852500677108765,
|
| 1045 |
+
"learning_rate": 0.0001883129646126818,
|
| 1046 |
+
"loss": 0.4142886161804199,
|
| 1047 |
+
"mean_token_accuracy": 0.8712429471313954,
|
| 1048 |
+
"num_tokens": 2333733.0,
|
| 1049 |
+
"step": 1000
|
| 1050 |
+
},
|
| 1051 |
+
{
|
| 1052 |
+
"epoch": 2.488169364881694,
|
| 1053 |
+
"eval_entropy": 0.5386548059624295,
|
| 1054 |
+
"eval_loss": 0.536101222038269,
|
| 1055 |
+
"eval_mean_token_accuracy": 0.8499491239009902,
|
| 1056 |
+
"eval_num_tokens": 2333733.0,
|
| 1057 |
+
"eval_runtime": 86.9501,
|
| 1058 |
+
"eval_samples_per_second": 15.825,
|
| 1059 |
+
"eval_steps_per_second": 1.978,
|
| 1060 |
+
"step": 1000
|
| 1061 |
+
},
|
| 1062 |
+
{
|
| 1063 |
+
"entropy": 0.4673406321555376,
|
| 1064 |
+
"epoch": 2.5379825653798256,
|
| 1065 |
+
"grad_norm": 0.7133921384811401,
|
| 1066 |
+
"learning_rate": 0.0001874326505341286,
|
| 1067 |
+
"loss": 0.40857529640197754,
|
| 1068 |
+
"mean_token_accuracy": 0.8747925907373428,
|
| 1069 |
+
"num_tokens": 2384270.0,
|
| 1070 |
+
"step": 1020
|
| 1071 |
+
},
|
| 1072 |
+
{
|
| 1073 |
+
"epoch": 2.5379825653798256,
|
| 1074 |
+
"eval_entropy": 0.495788364909416,
|
| 1075 |
+
"eval_loss": 0.5418923497200012,
|
| 1076 |
+
"eval_mean_token_accuracy": 0.851321972040243,
|
| 1077 |
+
"eval_num_tokens": 2384270.0,
|
| 1078 |
+
"eval_runtime": 86.7154,
|
| 1079 |
+
"eval_samples_per_second": 15.868,
|
| 1080 |
+
"eval_steps_per_second": 1.983,
|
| 1081 |
+
"step": 1020
|
| 1082 |
+
}
|
| 1083 |
+
],
|
| 1084 |
+
"logging_steps": 20,
|
| 1085 |
+
"max_steps": 4020,
|
| 1086 |
+
"num_input_tokens_seen": 0,
|
| 1087 |
+
"num_train_epochs": 10,
|
| 1088 |
+
"save_steps": 20,
|
| 1089 |
+
"stateful_callbacks": {
|
| 1090 |
+
"TrainerControl": {
|
| 1091 |
+
"args": {
|
| 1092 |
+
"should_epoch_stop": false,
|
| 1093 |
+
"should_evaluate": false,
|
| 1094 |
+
"should_log": false,
|
| 1095 |
+
"should_save": true,
|
| 1096 |
+
"should_training_stop": false
|
| 1097 |
+
},
|
| 1098 |
+
"attributes": {}
|
| 1099 |
+
}
|
| 1100 |
+
},
|
| 1101 |
+
"total_flos": 1.0076952699436032e+17,
|
| 1102 |
+
"train_batch_size": 4,
|
| 1103 |
+
"trial_name": null,
|
| 1104 |
+
"trial_params": null
|
| 1105 |
+
}
|
overgeneralisation_original_Swedish/Qwen3.5-4B-Base_overgeneralisation_splits_original_features_train_overgeneralisation_splits_original_features_test1/checkpoint-1040/README.md
ADDED
|
@@ -0,0 +1,209 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
---
|
| 2 |
+
base_model: Qwen/Qwen3.5-4B-Base
|
| 3 |
+
library_name: peft
|
| 4 |
+
pipeline_tag: text-generation
|
| 5 |
+
tags:
|
| 6 |
+
- base_model:adapter:Qwen/Qwen3.5-4B-Base
|
| 7 |
+
- lora
|
| 8 |
+
- sft
|
| 9 |
+
- transformers
|
| 10 |
+
- trl
|
| 11 |
+
---
|
| 12 |
+
|
| 13 |
+
# Model Card for Model ID
|
| 14 |
+
|
| 15 |
+
<!-- Provide a quick summary of what the model is/does. -->
|
| 16 |
+
|
| 17 |
+
|
| 18 |
+
|
| 19 |
+
## Model Details
|
| 20 |
+
|
| 21 |
+
### Model Description
|
| 22 |
+
|
| 23 |
+
<!-- Provide a longer summary of what this model is. -->
|
| 24 |
+
|
| 25 |
+
|
| 26 |
+
|
| 27 |
+
- **Developed by:** [More Information Needed]
|
| 28 |
+
- **Funded by [optional]:** [More Information Needed]
|
| 29 |
+
- **Shared by [optional]:** [More Information Needed]
|
| 30 |
+
- **Model type:** [More Information Needed]
|
| 31 |
+
- **Language(s) (NLP):** [More Information Needed]
|
| 32 |
+
- **License:** [More Information Needed]
|
| 33 |
+
- **Finetuned from model [optional]:** [More Information Needed]
|
| 34 |
+
|
| 35 |
+
### Model Sources [optional]
|
| 36 |
+
|
| 37 |
+
<!-- Provide the basic links for the model. -->
|
| 38 |
+
|
| 39 |
+
- **Repository:** [More Information Needed]
|
| 40 |
+
- **Paper [optional]:** [More Information Needed]
|
| 41 |
+
- **Demo [optional]:** [More Information Needed]
|
| 42 |
+
|
| 43 |
+
## Uses
|
| 44 |
+
|
| 45 |
+
<!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
|
| 46 |
+
|
| 47 |
+
### Direct Use
|
| 48 |
+
|
| 49 |
+
<!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
|
| 50 |
+
|
| 51 |
+
[More Information Needed]
|
| 52 |
+
|
| 53 |
+
### Downstream Use [optional]
|
| 54 |
+
|
| 55 |
+
<!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
|
| 56 |
+
|
| 57 |
+
[More Information Needed]
|
| 58 |
+
|
| 59 |
+
### Out-of-Scope Use
|
| 60 |
+
|
| 61 |
+
<!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
|
| 62 |
+
|
| 63 |
+
[More Information Needed]
|
| 64 |
+
|
| 65 |
+
## Bias, Risks, and Limitations
|
| 66 |
+
|
| 67 |
+
<!-- This section is meant to convey both technical and sociotechnical limitations. -->
|
| 68 |
+
|
| 69 |
+
[More Information Needed]
|
| 70 |
+
|
| 71 |
+
### Recommendations
|
| 72 |
+
|
| 73 |
+
<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
|
| 74 |
+
|
| 75 |
+
Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
|
| 76 |
+
|
| 77 |
+
## How to Get Started with the Model
|
| 78 |
+
|
| 79 |
+
Use the code below to get started with the model.
|
| 80 |
+
|
| 81 |
+
[More Information Needed]
|
| 82 |
+
|
| 83 |
+
## Training Details
|
| 84 |
+
|
| 85 |
+
### Training Data
|
| 86 |
+
|
| 87 |
+
<!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
|
| 88 |
+
|
| 89 |
+
[More Information Needed]
|
| 90 |
+
|
| 91 |
+
### Training Procedure
|
| 92 |
+
|
| 93 |
+
<!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
|
| 94 |
+
|
| 95 |
+
#### Preprocessing [optional]
|
| 96 |
+
|
| 97 |
+
[More Information Needed]
|
| 98 |
+
|
| 99 |
+
|
| 100 |
+
#### Training Hyperparameters
|
| 101 |
+
|
| 102 |
+
- **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
|
| 103 |
+
|
| 104 |
+
#### Speeds, Sizes, Times [optional]
|
| 105 |
+
|
| 106 |
+
<!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
|
| 107 |
+
|
| 108 |
+
[More Information Needed]
|
| 109 |
+
|
| 110 |
+
## Evaluation
|
| 111 |
+
|
| 112 |
+
<!-- This section describes the evaluation protocols and provides the results. -->
|
| 113 |
+
|
| 114 |
+
### Testing Data, Factors & Metrics
|
| 115 |
+
|
| 116 |
+
#### Testing Data
|
| 117 |
+
|
| 118 |
+
<!-- This should link to a Dataset Card if possible. -->
|
| 119 |
+
|
| 120 |
+
[More Information Needed]
|
| 121 |
+
|
| 122 |
+
#### Factors
|
| 123 |
+
|
| 124 |
+
<!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
|
| 125 |
+
|
| 126 |
+
[More Information Needed]
|
| 127 |
+
|
| 128 |
+
#### Metrics
|
| 129 |
+
|
| 130 |
+
<!-- These are the evaluation metrics being used, ideally with a description of why. -->
|
| 131 |
+
|
| 132 |
+
[More Information Needed]
|
| 133 |
+
|
| 134 |
+
### Results
|
| 135 |
+
|
| 136 |
+
[More Information Needed]
|
| 137 |
+
|
| 138 |
+
#### Summary
|
| 139 |
+
|
| 140 |
+
|
| 141 |
+
|
| 142 |
+
## Model Examination [optional]
|
| 143 |
+
|
| 144 |
+
<!-- Relevant interpretability work for the model goes here -->
|
| 145 |
+
|
| 146 |
+
[More Information Needed]
|
| 147 |
+
|
| 148 |
+
## Environmental Impact
|
| 149 |
+
|
| 150 |
+
<!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
|
| 151 |
+
|
| 152 |
+
Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
|
| 153 |
+
|
| 154 |
+
- **Hardware Type:** [More Information Needed]
|
| 155 |
+
- **Hours used:** [More Information Needed]
|
| 156 |
+
- **Cloud Provider:** [More Information Needed]
|
| 157 |
+
- **Compute Region:** [More Information Needed]
|
| 158 |
+
- **Carbon Emitted:** [More Information Needed]
|
| 159 |
+
|
| 160 |
+
## Technical Specifications [optional]
|
| 161 |
+
|
| 162 |
+
### Model Architecture and Objective
|
| 163 |
+
|
| 164 |
+
[More Information Needed]
|
| 165 |
+
|
| 166 |
+
### Compute Infrastructure
|
| 167 |
+
|
| 168 |
+
[More Information Needed]
|
| 169 |
+
|
| 170 |
+
#### Hardware
|
| 171 |
+
|
| 172 |
+
[More Information Needed]
|
| 173 |
+
|
| 174 |
+
#### Software
|
| 175 |
+
|
| 176 |
+
[More Information Needed]
|
| 177 |
+
|
| 178 |
+
## Citation [optional]
|
| 179 |
+
|
| 180 |
+
<!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
|
| 181 |
+
|
| 182 |
+
**BibTeX:**
|
| 183 |
+
|
| 184 |
+
[More Information Needed]
|
| 185 |
+
|
| 186 |
+
**APA:**
|
| 187 |
+
|
| 188 |
+
[More Information Needed]
|
| 189 |
+
|
| 190 |
+
## Glossary [optional]
|
| 191 |
+
|
| 192 |
+
<!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
|
| 193 |
+
|
| 194 |
+
[More Information Needed]
|
| 195 |
+
|
| 196 |
+
## More Information [optional]
|
| 197 |
+
|
| 198 |
+
[More Information Needed]
|
| 199 |
+
|
| 200 |
+
## Model Card Authors [optional]
|
| 201 |
+
|
| 202 |
+
[More Information Needed]
|
| 203 |
+
|
| 204 |
+
## Model Card Contact
|
| 205 |
+
|
| 206 |
+
[More Information Needed]
|
| 207 |
+
### Framework versions
|
| 208 |
+
|
| 209 |
+
- PEFT 0.18.1
|
overgeneralisation_original_Swedish/Qwen3.5-4B-Base_overgeneralisation_splits_original_features_train_overgeneralisation_splits_original_features_test1/checkpoint-1040/adapter_config.json
ADDED
|
@@ -0,0 +1,46 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
{
|
| 2 |
+
"alora_invocation_tokens": null,
|
| 3 |
+
"alpha_pattern": {},
|
| 4 |
+
"arrow_config": null,
|
| 5 |
+
"auto_mapping": null,
|
| 6 |
+
"base_model_name_or_path": "Qwen/Qwen3.5-4B-Base",
|
| 7 |
+
"bias": "none",
|
| 8 |
+
"corda_config": null,
|
| 9 |
+
"ensure_weight_tying": false,
|
| 10 |
+
"eva_config": null,
|
| 11 |
+
"exclude_modules": null,
|
| 12 |
+
"fan_in_fan_out": false,
|
| 13 |
+
"inference_mode": true,
|
| 14 |
+
"init_lora_weights": true,
|
| 15 |
+
"layer_replication": null,
|
| 16 |
+
"layers_pattern": null,
|
| 17 |
+
"layers_to_transform": null,
|
| 18 |
+
"loftq_config": {},
|
| 19 |
+
"lora_alpha": 256,
|
| 20 |
+
"lora_bias": false,
|
| 21 |
+
"lora_dropout": 0.0005183818805460705,
|
| 22 |
+
"megatron_config": null,
|
| 23 |
+
"megatron_core": "megatron.core",
|
| 24 |
+
"modules_to_save": null,
|
| 25 |
+
"peft_type": "LORA",
|
| 26 |
+
"peft_version": "0.18.1",
|
| 27 |
+
"qalora_group_size": 16,
|
| 28 |
+
"r": 128,
|
| 29 |
+
"rank_pattern": {},
|
| 30 |
+
"revision": null,
|
| 31 |
+
"target_modules": [
|
| 32 |
+
"up_proj",
|
| 33 |
+
"q_proj",
|
| 34 |
+
"o_proj",
|
| 35 |
+
"v_proj",
|
| 36 |
+
"k_proj",
|
| 37 |
+
"gate_proj",
|
| 38 |
+
"down_proj"
|
| 39 |
+
],
|
| 40 |
+
"target_parameters": null,
|
| 41 |
+
"task_type": "CAUSAL_LM",
|
| 42 |
+
"trainable_token_indices": null,
|
| 43 |
+
"use_dora": false,
|
| 44 |
+
"use_qalora": false,
|
| 45 |
+
"use_rslora": false
|
| 46 |
+
}
|
overgeneralisation_original_Swedish/Qwen3.5-4B-Base_overgeneralisation_splits_original_features_train_overgeneralisation_splits_original_features_test1/checkpoint-1040/chat_template.jinja
ADDED
|
@@ -0,0 +1,154 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
{%- set image_count = namespace(value=0) %}
|
| 2 |
+
{%- set video_count = namespace(value=0) %}
|
| 3 |
+
{%- macro render_content(content, do_vision_count, is_system_content=false) %}
|
| 4 |
+
{%- if content is string %}
|
| 5 |
+
{{- content }}
|
| 6 |
+
{%- elif content is iterable and content is not mapping %}
|
| 7 |
+
{%- for item in content %}
|
| 8 |
+
{%- if 'image' in item or 'image_url' in item or item.type == 'image' %}
|
| 9 |
+
{%- if is_system_content %}
|
| 10 |
+
{{- raise_exception('System message cannot contain images.') }}
|
| 11 |
+
{%- endif %}
|
| 12 |
+
{%- if do_vision_count %}
|
| 13 |
+
{%- set image_count.value = image_count.value + 1 %}
|
| 14 |
+
{%- endif %}
|
| 15 |
+
{%- if add_vision_id %}
|
| 16 |
+
{{- 'Picture ' ~ image_count.value ~ ': ' }}
|
| 17 |
+
{%- endif %}
|
| 18 |
+
{{- '<|vision_start|><|image_pad|><|vision_end|>' }}
|
| 19 |
+
{%- elif 'video' in item or item.type == 'video' %}
|
| 20 |
+
{%- if is_system_content %}
|
| 21 |
+
{{- raise_exception('System message cannot contain videos.') }}
|
| 22 |
+
{%- endif %}
|
| 23 |
+
{%- if do_vision_count %}
|
| 24 |
+
{%- set video_count.value = video_count.value + 1 %}
|
| 25 |
+
{%- endif %}
|
| 26 |
+
{%- if add_vision_id %}
|
| 27 |
+
{{- 'Video ' ~ video_count.value ~ ': ' }}
|
| 28 |
+
{%- endif %}
|
| 29 |
+
{{- '<|vision_start|><|video_pad|><|vision_end|>' }}
|
| 30 |
+
{%- elif 'text' in item %}
|
| 31 |
+
{{- item.text }}
|
| 32 |
+
{%- else %}
|
| 33 |
+
{{- raise_exception('Unexpected item type in content.') }}
|
| 34 |
+
{%- endif %}
|
| 35 |
+
{%- endfor %}
|
| 36 |
+
{%- elif content is none or content is undefined %}
|
| 37 |
+
{{- '' }}
|
| 38 |
+
{%- else %}
|
| 39 |
+
{{- raise_exception('Unexpected content type.') }}
|
| 40 |
+
{%- endif %}
|
| 41 |
+
{%- endmacro %}
|
| 42 |
+
{%- if not messages %}
|
| 43 |
+
{{- raise_exception('No messages provided.') }}
|
| 44 |
+
{%- endif %}
|
| 45 |
+
{%- if tools and tools is iterable and tools is not mapping %}
|
| 46 |
+
{{- '<|im_start|>system\n' }}
|
| 47 |
+
{{- "# Tools\n\nYou have access to the following functions:\n\n<tools>" }}
|
| 48 |
+
{%- for tool in tools %}
|
| 49 |
+
{{- "\n" }}
|
| 50 |
+
{{- tool | tojson }}
|
| 51 |
+
{%- endfor %}
|
| 52 |
+
{{- "\n</tools>" }}
|
| 53 |
+
{{- '\n\nIf you choose to call a function ONLY reply in the following format with NO suffix:\n\n<tool_call>\n<function=example_function_name>\n<parameter=example_parameter_1>\nvalue_1\n</parameter>\n<parameter=example_parameter_2>\nThis is the value for the second parameter\nthat can span\nmultiple lines\n</parameter>\n</function>\n</tool_call>\n\n<IMPORTANT>\nReminder:\n- Function calls MUST follow the specified format: an inner <function=...></function> block must be nested within <tool_call></tool_call> XML tags\n- Required parameters MUST be specified\n- You may provide optional reasoning for your function call in natural language BEFORE the function call, but NOT after\n- If there is no function call available, answer the question like normal with your current knowledge and do not tell the user about function calls\n</IMPORTANT>' }}
|
| 54 |
+
{%- if messages[0].role == 'system' %}
|
| 55 |
+
{%- set content = render_content(messages[0].content, false, true)|trim %}
|
| 56 |
+
{%- if content %}
|
| 57 |
+
{{- '\n\n' + content }}
|
| 58 |
+
{%- endif %}
|
| 59 |
+
{%- endif %}
|
| 60 |
+
{{- '<|im_end|>\n' }}
|
| 61 |
+
{%- else %}
|
| 62 |
+
{%- if messages[0].role == 'system' %}
|
| 63 |
+
{%- set content = render_content(messages[0].content, false, true)|trim %}
|
| 64 |
+
{{- '<|im_start|>system\n' + content + '<|im_end|>\n' }}
|
| 65 |
+
{%- endif %}
|
| 66 |
+
{%- endif %}
|
| 67 |
+
{%- set ns = namespace(multi_step_tool=true, last_query_index=messages|length - 1) %}
|
| 68 |
+
{%- for message in messages[::-1] %}
|
| 69 |
+
{%- set index = (messages|length - 1) - loop.index0 %}
|
| 70 |
+
{%- if ns.multi_step_tool and message.role == "user" %}
|
| 71 |
+
{%- set content = render_content(message.content, false)|trim %}
|
| 72 |
+
{%- if not(content.startswith('<tool_response>') and content.endswith('</tool_response>')) %}
|
| 73 |
+
{%- set ns.multi_step_tool = false %}
|
| 74 |
+
{%- set ns.last_query_index = index %}
|
| 75 |
+
{%- endif %}
|
| 76 |
+
{%- endif %}
|
| 77 |
+
{%- endfor %}
|
| 78 |
+
{%- if ns.multi_step_tool %}
|
| 79 |
+
{{- raise_exception('No user query found in messages.') }}
|
| 80 |
+
{%- endif %}
|
| 81 |
+
{%- for message in messages %}
|
| 82 |
+
{%- set content = render_content(message.content, true)|trim %}
|
| 83 |
+
{%- if message.role == "system" %}
|
| 84 |
+
{%- if not loop.first %}
|
| 85 |
+
{{- raise_exception('System message must be at the beginning.') }}
|
| 86 |
+
{%- endif %}
|
| 87 |
+
{%- elif message.role == "user" %}
|
| 88 |
+
{{- '<|im_start|>' + message.role + '\n' + content + '<|im_end|>' + '\n' }}
|
| 89 |
+
{%- elif message.role == "assistant" %}
|
| 90 |
+
{%- set reasoning_content = '' %}
|
| 91 |
+
{%- if message.reasoning_content is string %}
|
| 92 |
+
{%- set reasoning_content = message.reasoning_content %}
|
| 93 |
+
{%- else %}
|
| 94 |
+
{%- if '</think>' in content %}
|
| 95 |
+
{%- set reasoning_content = content.split('</think>')[0].rstrip('\n').split('<think>')[-1].lstrip('\n') %}
|
| 96 |
+
{%- set content = content.split('</think>')[-1].lstrip('\n') %}
|
| 97 |
+
{%- endif %}
|
| 98 |
+
{%- endif %}
|
| 99 |
+
{%- set reasoning_content = reasoning_content|trim %}
|
| 100 |
+
{%- if loop.index0 > ns.last_query_index %}
|
| 101 |
+
{{- '<|im_start|>' + message.role + '\n<think>\n' + reasoning_content + '\n</think>\n\n' + content }}
|
| 102 |
+
{%- else %}
|
| 103 |
+
{{- '<|im_start|>' + message.role + '\n' + content }}
|
| 104 |
+
{%- endif %}
|
| 105 |
+
{%- if message.tool_calls and message.tool_calls is iterable and message.tool_calls is not mapping %}
|
| 106 |
+
{%- for tool_call in message.tool_calls %}
|
| 107 |
+
{%- if tool_call.function is defined %}
|
| 108 |
+
{%- set tool_call = tool_call.function %}
|
| 109 |
+
{%- endif %}
|
| 110 |
+
{%- if loop.first %}
|
| 111 |
+
{%- if content|trim %}
|
| 112 |
+
{{- '\n\n<tool_call>\n<function=' + tool_call.name + '>\n' }}
|
| 113 |
+
{%- else %}
|
| 114 |
+
{{- '<tool_call>\n<function=' + tool_call.name + '>\n' }}
|
| 115 |
+
{%- endif %}
|
| 116 |
+
{%- else %}
|
| 117 |
+
{{- '\n<tool_call>\n<function=' + tool_call.name + '>\n' }}
|
| 118 |
+
{%- endif %}
|
| 119 |
+
{%- if tool_call.arguments is defined %}
|
| 120 |
+
{%- for args_name, args_value in tool_call.arguments|items %}
|
| 121 |
+
{{- '<parameter=' + args_name + '>\n' }}
|
| 122 |
+
{%- set args_value = args_value | tojson | safe if args_value is mapping or (args_value is sequence and args_value is not string) else args_value | string %}
|
| 123 |
+
{{- args_value }}
|
| 124 |
+
{{- '\n</parameter>\n' }}
|
| 125 |
+
{%- endfor %}
|
| 126 |
+
{%- endif %}
|
| 127 |
+
{{- '</function>\n</tool_call>' }}
|
| 128 |
+
{%- endfor %}
|
| 129 |
+
{%- endif %}
|
| 130 |
+
{{- '<|im_end|>\n' }}
|
| 131 |
+
{%- elif message.role == "tool" %}
|
| 132 |
+
{%- if loop.previtem and loop.previtem.role != "tool" %}
|
| 133 |
+
{{- '<|im_start|>user' }}
|
| 134 |
+
{%- endif %}
|
| 135 |
+
{{- '\n<tool_response>\n' }}
|
| 136 |
+
{{- content }}
|
| 137 |
+
{{- '\n</tool_response>' }}
|
| 138 |
+
{%- if not loop.last and loop.nextitem.role != "tool" %}
|
| 139 |
+
{{- '<|im_end|>\n' }}
|
| 140 |
+
{%- elif loop.last %}
|
| 141 |
+
{{- '<|im_end|>\n' }}
|
| 142 |
+
{%- endif %}
|
| 143 |
+
{%- else %}
|
| 144 |
+
{{- raise_exception('Unexpected message role.') }}
|
| 145 |
+
{%- endif %}
|
| 146 |
+
{%- endfor %}
|
| 147 |
+
{%- if add_generation_prompt %}
|
| 148 |
+
{{- '<|im_start|>assistant\n' }}
|
| 149 |
+
{%- if enable_thinking is defined and enable_thinking is false %}
|
| 150 |
+
{{- '<think>\n\n</think>\n\n' }}
|
| 151 |
+
{%- else %}
|
| 152 |
+
{{- '<think>\n' }}
|
| 153 |
+
{%- endif %}
|
| 154 |
+
{%- endif %}
|
overgeneralisation_original_Swedish/Qwen3.5-4B-Base_overgeneralisation_splits_original_features_train_overgeneralisation_splits_original_features_test1/checkpoint-1040/tokenizer_config.json
ADDED
|
@@ -0,0 +1,31 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
{
|
| 2 |
+
"add_prefix_space": false,
|
| 3 |
+
"audio_bos_token": "<|audio_start|>",
|
| 4 |
+
"audio_eos_token": "<|audio_end|>",
|
| 5 |
+
"audio_token": "<|audio_pad|>",
|
| 6 |
+
"backend": "tokenizers",
|
| 7 |
+
"bos_token": null,
|
| 8 |
+
"clean_up_tokenization_spaces": false,
|
| 9 |
+
"eos_token": "<|endoftext|>",
|
| 10 |
+
"errors": "replace",
|
| 11 |
+
"image_token": "<|image_pad|>",
|
| 12 |
+
"is_local": false,
|
| 13 |
+
"model_max_length": 262144,
|
| 14 |
+
"model_specific_special_tokens": {
|
| 15 |
+
"audio_bos_token": "<|audio_start|>",
|
| 16 |
+
"audio_eos_token": "<|audio_end|>",
|
| 17 |
+
"audio_token": "<|audio_pad|>",
|
| 18 |
+
"image_token": "<|image_pad|>",
|
| 19 |
+
"video_token": "<|video_pad|>",
|
| 20 |
+
"vision_bos_token": "<|vision_start|>",
|
| 21 |
+
"vision_eos_token": "<|vision_end|>"
|
| 22 |
+
},
|
| 23 |
+
"pad_token": "<|endoftext|>",
|
| 24 |
+
"pretokenize_regex": "(?i:'s|'t|'re|'ve|'m|'ll|'d)|[^\\r\\n\\p{L}\\p{N}]?[\\p{L}\\p{M}]+|\\p{N}| ?[^\\s\\p{L}\\p{M}\\p{N}]+[\\r\\n]*|\\s*[\\r\\n]+|\\s+(?!\\S)|\\s+",
|
| 25 |
+
"split_special_tokens": false,
|
| 26 |
+
"tokenizer_class": "TokenizersBackend",
|
| 27 |
+
"unk_token": null,
|
| 28 |
+
"video_token": "<|video_pad|>",
|
| 29 |
+
"vision_bos_token": "<|vision_start|>",
|
| 30 |
+
"vision_eos_token": "<|vision_end|>"
|
| 31 |
+
}
|
overgeneralisation_original_Swedish/Qwen3.5-4B-Base_overgeneralisation_splits_original_features_train_overgeneralisation_splits_original_features_test1/checkpoint-1040/trainer_state.json
ADDED
|
@@ -0,0 +1,1126 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
{
|
| 2 |
+
"best_global_step": null,
|
| 3 |
+
"best_metric": null,
|
| 4 |
+
"best_model_checkpoint": null,
|
| 5 |
+
"epoch": 2.587795765877958,
|
| 6 |
+
"eval_steps": 20,
|
| 7 |
+
"global_step": 1040,
|
| 8 |
+
"is_hyper_param_search": false,
|
| 9 |
+
"is_local_process_zero": true,
|
| 10 |
+
"is_world_process_zero": true,
|
| 11 |
+
"log_history": [
|
| 12 |
+
{
|
| 13 |
+
"entropy": 1.9784346982836722,
|
| 14 |
+
"epoch": 0.049813200498132,
|
| 15 |
+
"grad_norm": 3.0229668617248535,
|
| 16 |
+
"learning_rate": 9.526142962415369e-06,
|
| 17 |
+
"loss": 1.7360023498535155,
|
| 18 |
+
"mean_token_accuracy": 0.6449888605624438,
|
| 19 |
+
"num_tokens": 46794.0,
|
| 20 |
+
"step": 20
|
| 21 |
+
},
|
| 22 |
+
{
|
| 23 |
+
"epoch": 0.049813200498132,
|
| 24 |
+
"eval_entropy": 1.41506897571475,
|
| 25 |
+
"eval_loss": 1.1876318454742432,
|
| 26 |
+
"eval_mean_token_accuracy": 0.734131895525511,
|
| 27 |
+
"eval_num_tokens": 46794.0,
|
| 28 |
+
"eval_runtime": 87.8071,
|
| 29 |
+
"eval_samples_per_second": 15.671,
|
| 30 |
+
"eval_steps_per_second": 1.959,
|
| 31 |
+
"step": 20
|
| 32 |
+
},
|
| 33 |
+
{
|
| 34 |
+
"entropy": 1.049924298375845,
|
| 35 |
+
"epoch": 0.099626400996264,
|
| 36 |
+
"grad_norm": 1.5795097351074219,
|
| 37 |
+
"learning_rate": 1.9553661870221022e-05,
|
| 38 |
+
"loss": 0.8944448471069336,
|
| 39 |
+
"mean_token_accuracy": 0.7748479396104813,
|
| 40 |
+
"num_tokens": 90754.0,
|
| 41 |
+
"step": 40
|
| 42 |
+
},
|
| 43 |
+
{
|
| 44 |
+
"epoch": 0.099626400996264,
|
| 45 |
+
"eval_entropy": 0.7996658658565476,
|
| 46 |
+
"eval_loss": 0.7202735543251038,
|
| 47 |
+
"eval_mean_token_accuracy": 0.8070558306089667,
|
| 48 |
+
"eval_num_tokens": 90754.0,
|
| 49 |
+
"eval_runtime": 86.9199,
|
| 50 |
+
"eval_samples_per_second": 15.831,
|
| 51 |
+
"eval_steps_per_second": 1.979,
|
| 52 |
+
"step": 40
|
| 53 |
+
},
|
| 54 |
+
{
|
| 55 |
+
"entropy": 0.7734908878803253,
|
| 56 |
+
"epoch": 0.149439601494396,
|
| 57 |
+
"grad_norm": 1.3136248588562012,
|
| 58 |
+
"learning_rate": 2.9581180778026673e-05,
|
| 59 |
+
"loss": 0.6780608654022217,
|
| 60 |
+
"mean_token_accuracy": 0.8168170280754566,
|
| 61 |
+
"num_tokens": 137472.0,
|
| 62 |
+
"step": 60
|
| 63 |
+
},
|
| 64 |
+
{
|
| 65 |
+
"epoch": 0.149439601494396,
|
| 66 |
+
"eval_entropy": 0.7119324009778888,
|
| 67 |
+
"eval_loss": 0.6554311513900757,
|
| 68 |
+
"eval_mean_token_accuracy": 0.8215604798738346,
|
| 69 |
+
"eval_num_tokens": 137472.0,
|
| 70 |
+
"eval_runtime": 86.8692,
|
| 71 |
+
"eval_samples_per_second": 15.84,
|
| 72 |
+
"eval_steps_per_second": 1.98,
|
| 73 |
+
"step": 60
|
| 74 |
+
},
|
| 75 |
+
{
|
| 76 |
+
"entropy": 0.7071127541363239,
|
| 77 |
+
"epoch": 0.199252801992528,
|
| 78 |
+
"grad_norm": 1.387060284614563,
|
| 79 |
+
"learning_rate": 3.960869968583232e-05,
|
| 80 |
+
"loss": 0.6382100582122803,
|
| 81 |
+
"mean_token_accuracy": 0.8229366384446621,
|
| 82 |
+
"num_tokens": 187408.0,
|
| 83 |
+
"step": 80
|
| 84 |
+
},
|
| 85 |
+
{
|
| 86 |
+
"epoch": 0.199252801992528,
|
| 87 |
+
"eval_entropy": 0.6883931482254073,
|
| 88 |
+
"eval_loss": 0.625065803527832,
|
| 89 |
+
"eval_mean_token_accuracy": 0.828940509710201,
|
| 90 |
+
"eval_num_tokens": 187408.0,
|
| 91 |
+
"eval_runtime": 86.662,
|
| 92 |
+
"eval_samples_per_second": 15.878,
|
| 93 |
+
"eval_steps_per_second": 1.985,
|
| 94 |
+
"step": 80
|
| 95 |
+
},
|
| 96 |
+
{
|
| 97 |
+
"entropy": 0.6800824083387852,
|
| 98 |
+
"epoch": 0.24906600249066002,
|
| 99 |
+
"grad_norm": 0.9892916679382324,
|
| 100 |
+
"learning_rate": 4.963621859363797e-05,
|
| 101 |
+
"loss": 0.6011715888977051,
|
| 102 |
+
"mean_token_accuracy": 0.8323964163661003,
|
| 103 |
+
"num_tokens": 234197.0,
|
| 104 |
+
"step": 100
|
| 105 |
+
},
|
| 106 |
+
{
|
| 107 |
+
"epoch": 0.24906600249066002,
|
| 108 |
+
"eval_entropy": 0.6840810470802839,
|
| 109 |
+
"eval_loss": 0.6037028431892395,
|
| 110 |
+
"eval_mean_token_accuracy": 0.8309669033732525,
|
| 111 |
+
"eval_num_tokens": 234197.0,
|
| 112 |
+
"eval_runtime": 86.4637,
|
| 113 |
+
"eval_samples_per_second": 15.914,
|
| 114 |
+
"eval_steps_per_second": 1.989,
|
| 115 |
+
"step": 100
|
| 116 |
+
},
|
| 117 |
+
{
|
| 118 |
+
"entropy": 0.6776216626167297,
|
| 119 |
+
"epoch": 0.298879202988792,
|
| 120 |
+
"grad_norm": 0.8918434977531433,
|
| 121 |
+
"learning_rate": 5.9663737501443624e-05,
|
| 122 |
+
"loss": 0.5991742610931396,
|
| 123 |
+
"mean_token_accuracy": 0.8300838828086853,
|
| 124 |
+
"num_tokens": 281241.0,
|
| 125 |
+
"step": 120
|
| 126 |
+
},
|
| 127 |
+
{
|
| 128 |
+
"epoch": 0.298879202988792,
|
| 129 |
+
"eval_entropy": 0.690427724705186,
|
| 130 |
+
"eval_loss": 0.5939701795578003,
|
| 131 |
+
"eval_mean_token_accuracy": 0.8345950186945671,
|
| 132 |
+
"eval_num_tokens": 281241.0,
|
| 133 |
+
"eval_runtime": 86.6626,
|
| 134 |
+
"eval_samples_per_second": 15.878,
|
| 135 |
+
"eval_steps_per_second": 1.985,
|
| 136 |
+
"step": 120
|
| 137 |
+
},
|
| 138 |
+
{
|
| 139 |
+
"entropy": 0.6709842771291733,
|
| 140 |
+
"epoch": 0.34869240348692404,
|
| 141 |
+
"grad_norm": 0.9135531187057495,
|
| 142 |
+
"learning_rate": 6.969125640924927e-05,
|
| 143 |
+
"loss": 0.5914147377014161,
|
| 144 |
+
"mean_token_accuracy": 0.8314545609056949,
|
| 145 |
+
"num_tokens": 327393.0,
|
| 146 |
+
"step": 140
|
| 147 |
+
},
|
| 148 |
+
{
|
| 149 |
+
"epoch": 0.34869240348692404,
|
| 150 |
+
"eval_entropy": 0.6584504666023476,
|
| 151 |
+
"eval_loss": 0.5849721431732178,
|
| 152 |
+
"eval_mean_token_accuracy": 0.8357757236375365,
|
| 153 |
+
"eval_num_tokens": 327393.0,
|
| 154 |
+
"eval_runtime": 86.3262,
|
| 155 |
+
"eval_samples_per_second": 15.94,
|
| 156 |
+
"eval_steps_per_second": 1.992,
|
| 157 |
+
"step": 140
|
| 158 |
+
},
|
| 159 |
+
{
|
| 160 |
+
"entropy": 0.6524647936224938,
|
| 161 |
+
"epoch": 0.398505603985056,
|
| 162 |
+
"grad_norm": 0.8651587963104248,
|
| 163 |
+
"learning_rate": 7.971877531705493e-05,
|
| 164 |
+
"loss": 0.5710843563079834,
|
| 165 |
+
"mean_token_accuracy": 0.8396127380430698,
|
| 166 |
+
"num_tokens": 373834.0,
|
| 167 |
+
"step": 160
|
| 168 |
+
},
|
| 169 |
+
{
|
| 170 |
+
"epoch": 0.398505603985056,
|
| 171 |
+
"eval_entropy": 0.6283470298661742,
|
| 172 |
+
"eval_loss": 0.5738973617553711,
|
| 173 |
+
"eval_mean_token_accuracy": 0.8379981181649274,
|
| 174 |
+
"eval_num_tokens": 373834.0,
|
| 175 |
+
"eval_runtime": 86.5619,
|
| 176 |
+
"eval_samples_per_second": 15.896,
|
| 177 |
+
"eval_steps_per_second": 1.987,
|
| 178 |
+
"step": 160
|
| 179 |
+
},
|
| 180 |
+
{
|
| 181 |
+
"entropy": 0.6450445972383022,
|
| 182 |
+
"epoch": 0.44831880448318806,
|
| 183 |
+
"grad_norm": 0.8661723732948303,
|
| 184 |
+
"learning_rate": 8.974629422486058e-05,
|
| 185 |
+
"loss": 0.5677794933319091,
|
| 186 |
+
"mean_token_accuracy": 0.8389350369572639,
|
| 187 |
+
"num_tokens": 422572.0,
|
| 188 |
+
"step": 180
|
| 189 |
+
},
|
| 190 |
+
{
|
| 191 |
+
"epoch": 0.44831880448318806,
|
| 192 |
+
"eval_entropy": 0.6142613257086554,
|
| 193 |
+
"eval_loss": 0.5698265433311462,
|
| 194 |
+
"eval_mean_token_accuracy": 0.8388577273418737,
|
| 195 |
+
"eval_num_tokens": 422572.0,
|
| 196 |
+
"eval_runtime": 86.4443,
|
| 197 |
+
"eval_samples_per_second": 15.918,
|
| 198 |
+
"eval_steps_per_second": 1.99,
|
| 199 |
+
"step": 180
|
| 200 |
+
},
|
| 201 |
+
{
|
| 202 |
+
"entropy": 0.6448334597051144,
|
| 203 |
+
"epoch": 0.49813200498132004,
|
| 204 |
+
"grad_norm": 0.9662242531776428,
|
| 205 |
+
"learning_rate": 9.977381313266624e-05,
|
| 206 |
+
"loss": 0.581433916091919,
|
| 207 |
+
"mean_token_accuracy": 0.8387043006718159,
|
| 208 |
+
"num_tokens": 471879.0,
|
| 209 |
+
"step": 200
|
| 210 |
+
},
|
| 211 |
+
{
|
| 212 |
+
"epoch": 0.49813200498132004,
|
| 213 |
+
"eval_entropy": 0.6154296522916749,
|
| 214 |
+
"eval_loss": 0.5660303831100464,
|
| 215 |
+
"eval_mean_token_accuracy": 0.8412494766850804,
|
| 216 |
+
"eval_num_tokens": 471879.0,
|
| 217 |
+
"eval_runtime": 86.3063,
|
| 218 |
+
"eval_samples_per_second": 15.943,
|
| 219 |
+
"eval_steps_per_second": 1.993,
|
| 220 |
+
"step": 200
|
| 221 |
+
},
|
| 222 |
+
{
|
| 223 |
+
"entropy": 0.6376728117465973,
|
| 224 |
+
"epoch": 0.547945205479452,
|
| 225 |
+
"grad_norm": 0.7618638873100281,
|
| 226 |
+
"learning_rate": 0.00010980133204047189,
|
| 227 |
+
"loss": 0.5678351402282715,
|
| 228 |
+
"mean_token_accuracy": 0.8404546812176704,
|
| 229 |
+
"num_tokens": 520984.0,
|
| 230 |
+
"step": 220
|
| 231 |
+
},
|
| 232 |
+
{
|
| 233 |
+
"epoch": 0.547945205479452,
|
| 234 |
+
"eval_entropy": 0.6181817033956217,
|
| 235 |
+
"eval_loss": 0.5663750171661377,
|
| 236 |
+
"eval_mean_token_accuracy": 0.8388350962899452,
|
| 237 |
+
"eval_num_tokens": 520984.0,
|
| 238 |
+
"eval_runtime": 86.5904,
|
| 239 |
+
"eval_samples_per_second": 15.891,
|
| 240 |
+
"eval_steps_per_second": 1.986,
|
| 241 |
+
"step": 220
|
| 242 |
+
},
|
| 243 |
+
{
|
| 244 |
+
"entropy": 0.6303176879882812,
|
| 245 |
+
"epoch": 0.597758405977584,
|
| 246 |
+
"grad_norm": 0.7571695446968079,
|
| 247 |
+
"learning_rate": 0.00011982885094827753,
|
| 248 |
+
"loss": 0.5502778053283691,
|
| 249 |
+
"mean_token_accuracy": 0.8429657347500324,
|
| 250 |
+
"num_tokens": 566596.0,
|
| 251 |
+
"step": 240
|
| 252 |
+
},
|
| 253 |
+
{
|
| 254 |
+
"epoch": 0.597758405977584,
|
| 255 |
+
"eval_entropy": 0.6252533817707107,
|
| 256 |
+
"eval_loss": 0.5570284128189087,
|
| 257 |
+
"eval_mean_token_accuracy": 0.8427327847064927,
|
| 258 |
+
"eval_num_tokens": 566596.0,
|
| 259 |
+
"eval_runtime": 86.4157,
|
| 260 |
+
"eval_samples_per_second": 15.923,
|
| 261 |
+
"eval_steps_per_second": 1.99,
|
| 262 |
+
"step": 240
|
| 263 |
+
},
|
| 264 |
+
{
|
| 265 |
+
"entropy": 0.6202544964849949,
|
| 266 |
+
"epoch": 0.6475716064757161,
|
| 267 |
+
"grad_norm": 0.6447190642356873,
|
| 268 |
+
"learning_rate": 0.00012985636985608318,
|
| 269 |
+
"loss": 0.5485352993011474,
|
| 270 |
+
"mean_token_accuracy": 0.844165726006031,
|
| 271 |
+
"num_tokens": 613603.0,
|
| 272 |
+
"step": 260
|
| 273 |
+
},
|
| 274 |
+
{
|
| 275 |
+
"epoch": 0.6475716064757161,
|
| 276 |
+
"eval_entropy": 0.6441633552312851,
|
| 277 |
+
"eval_loss": 0.5606644153594971,
|
| 278 |
+
"eval_mean_token_accuracy": 0.842403513054515,
|
| 279 |
+
"eval_num_tokens": 613603.0,
|
| 280 |
+
"eval_runtime": 86.6343,
|
| 281 |
+
"eval_samples_per_second": 15.883,
|
| 282 |
+
"eval_steps_per_second": 1.985,
|
| 283 |
+
"step": 260
|
| 284 |
+
},
|
| 285 |
+
{
|
| 286 |
+
"entropy": 0.6306711677461863,
|
| 287 |
+
"epoch": 0.6973848069738481,
|
| 288 |
+
"grad_norm": 0.7869907021522522,
|
| 289 |
+
"learning_rate": 0.00013988388876388883,
|
| 290 |
+
"loss": 0.5579307556152344,
|
| 291 |
+
"mean_token_accuracy": 0.841247134655714,
|
| 292 |
+
"num_tokens": 658565.0,
|
| 293 |
+
"step": 280
|
| 294 |
+
},
|
| 295 |
+
{
|
| 296 |
+
"epoch": 0.6973848069738481,
|
| 297 |
+
"eval_entropy": 0.6263934678809587,
|
| 298 |
+
"eval_loss": 0.5559113025665283,
|
| 299 |
+
"eval_mean_token_accuracy": 0.8427334743183713,
|
| 300 |
+
"eval_num_tokens": 658565.0,
|
| 301 |
+
"eval_runtime": 86.6403,
|
| 302 |
+
"eval_samples_per_second": 15.882,
|
| 303 |
+
"eval_steps_per_second": 1.985,
|
| 304 |
+
"step": 280
|
| 305 |
+
},
|
| 306 |
+
{
|
| 307 |
+
"entropy": 0.6385872110724449,
|
| 308 |
+
"epoch": 0.7471980074719801,
|
| 309 |
+
"grad_norm": 0.6679229736328125,
|
| 310 |
+
"learning_rate": 0.0001499114076716945,
|
| 311 |
+
"loss": 0.5667279720306396,
|
| 312 |
+
"mean_token_accuracy": 0.8389136254787445,
|
| 313 |
+
"num_tokens": 705680.0,
|
| 314 |
+
"step": 300
|
| 315 |
+
},
|
| 316 |
+
{
|
| 317 |
+
"epoch": 0.7471980074719801,
|
| 318 |
+
"eval_entropy": 0.6141417321077612,
|
| 319 |
+
"eval_loss": 0.5570600628852844,
|
| 320 |
+
"eval_mean_token_accuracy": 0.8437647996253745,
|
| 321 |
+
"eval_num_tokens": 705680.0,
|
| 322 |
+
"eval_runtime": 86.7588,
|
| 323 |
+
"eval_samples_per_second": 15.86,
|
| 324 |
+
"eval_steps_per_second": 1.983,
|
| 325 |
+
"step": 300
|
| 326 |
+
},
|
| 327 |
+
{
|
| 328 |
+
"entropy": 0.6199494235217571,
|
| 329 |
+
"epoch": 0.797011207970112,
|
| 330 |
+
"grad_norm": 0.7924400568008423,
|
| 331 |
+
"learning_rate": 0.00015993892657950015,
|
| 332 |
+
"loss": 0.5529299736022949,
|
| 333 |
+
"mean_token_accuracy": 0.8426973208785057,
|
| 334 |
+
"num_tokens": 752616.0,
|
| 335 |
+
"step": 320
|
| 336 |
+
},
|
| 337 |
+
{
|
| 338 |
+
"epoch": 0.797011207970112,
|
| 339 |
+
"eval_entropy": 0.6133768925833147,
|
| 340 |
+
"eval_loss": 0.556602418422699,
|
| 341 |
+
"eval_mean_token_accuracy": 0.8432947965555413,
|
| 342 |
+
"eval_num_tokens": 752616.0,
|
| 343 |
+
"eval_runtime": 86.492,
|
| 344 |
+
"eval_samples_per_second": 15.909,
|
| 345 |
+
"eval_steps_per_second": 1.989,
|
| 346 |
+
"step": 320
|
| 347 |
+
},
|
| 348 |
+
{
|
| 349 |
+
"entropy": 0.6203986253589392,
|
| 350 |
+
"epoch": 0.8468244084682441,
|
| 351 |
+
"grad_norm": 0.8364354372024536,
|
| 352 |
+
"learning_rate": 0.00016996644548730578,
|
| 353 |
+
"loss": 0.5551144123077393,
|
| 354 |
+
"mean_token_accuracy": 0.8432973213493824,
|
| 355 |
+
"num_tokens": 797151.0,
|
| 356 |
+
"step": 340
|
| 357 |
+
},
|
| 358 |
+
{
|
| 359 |
+
"epoch": 0.8468244084682441,
|
| 360 |
+
"eval_entropy": 0.6017442844634833,
|
| 361 |
+
"eval_loss": 0.5566568374633789,
|
| 362 |
+
"eval_mean_token_accuracy": 0.8437666123689607,
|
| 363 |
+
"eval_num_tokens": 797151.0,
|
| 364 |
+
"eval_runtime": 86.5552,
|
| 365 |
+
"eval_samples_per_second": 15.897,
|
| 366 |
+
"eval_steps_per_second": 1.987,
|
| 367 |
+
"step": 340
|
| 368 |
+
},
|
| 369 |
+
{
|
| 370 |
+
"entropy": 0.6341533534228802,
|
| 371 |
+
"epoch": 0.8966376089663761,
|
| 372 |
+
"grad_norm": 0.7783445715904236,
|
| 373 |
+
"learning_rate": 0.00017999396439511144,
|
| 374 |
+
"loss": 0.5669133186340332,
|
| 375 |
+
"mean_token_accuracy": 0.8379446342587471,
|
| 376 |
+
"num_tokens": 843585.0,
|
| 377 |
+
"step": 360
|
| 378 |
+
},
|
| 379 |
+
{
|
| 380 |
+
"epoch": 0.8966376089663761,
|
| 381 |
+
"eval_entropy": 0.6055107958788095,
|
| 382 |
+
"eval_loss": 0.5599350333213806,
|
| 383 |
+
"eval_mean_token_accuracy": 0.8435030894917112,
|
| 384 |
+
"eval_num_tokens": 843585.0,
|
| 385 |
+
"eval_runtime": 86.4814,
|
| 386 |
+
"eval_samples_per_second": 15.911,
|
| 387 |
+
"eval_steps_per_second": 1.989,
|
| 388 |
+
"step": 360
|
| 389 |
+
},
|
| 390 |
+
{
|
| 391 |
+
"entropy": 0.6306198488920927,
|
| 392 |
+
"epoch": 0.9464508094645081,
|
| 393 |
+
"grad_norm": 0.8449786901473999,
|
| 394 |
+
"learning_rate": 0.0001900214833029171,
|
| 395 |
+
"loss": 0.5739435195922852,
|
| 396 |
+
"mean_token_accuracy": 0.8393832489848136,
|
| 397 |
+
"num_tokens": 889842.0,
|
| 398 |
+
"step": 380
|
| 399 |
+
},
|
| 400 |
+
{
|
| 401 |
+
"epoch": 0.9464508094645081,
|
| 402 |
+
"eval_entropy": 0.6129532439071078,
|
| 403 |
+
"eval_loss": 0.5566295981407166,
|
| 404 |
+
"eval_mean_token_accuracy": 0.8430350880290187,
|
| 405 |
+
"eval_num_tokens": 889842.0,
|
| 406 |
+
"eval_runtime": 86.4643,
|
| 407 |
+
"eval_samples_per_second": 15.914,
|
| 408 |
+
"eval_steps_per_second": 1.989,
|
| 409 |
+
"step": 380
|
| 410 |
+
},
|
| 411 |
+
{
|
| 412 |
+
"entropy": 0.6203123550862074,
|
| 413 |
+
"epoch": 0.9962640099626401,
|
| 414 |
+
"grad_norm": 0.7334314584732056,
|
| 415 |
+
"learning_rate": 0.00020004900221072276,
|
| 416 |
+
"loss": 0.5547565937042236,
|
| 417 |
+
"mean_token_accuracy": 0.8403573960065842,
|
| 418 |
+
"num_tokens": 935589.0,
|
| 419 |
+
"step": 400
|
| 420 |
+
},
|
| 421 |
+
{
|
| 422 |
+
"epoch": 0.9962640099626401,
|
| 423 |
+
"eval_entropy": 0.6275761647279873,
|
| 424 |
+
"eval_loss": 0.5621116757392883,
|
| 425 |
+
"eval_mean_token_accuracy": 0.841587379228237,
|
| 426 |
+
"eval_num_tokens": 935589.0,
|
| 427 |
+
"eval_runtime": 86.4748,
|
| 428 |
+
"eval_samples_per_second": 15.912,
|
| 429 |
+
"eval_steps_per_second": 1.989,
|
| 430 |
+
"step": 400
|
| 431 |
+
},
|
| 432 |
+
{
|
| 433 |
+
"entropy": 0.5795013002860241,
|
| 434 |
+
"epoch": 1.0448318804483188,
|
| 435 |
+
"grad_norm": 0.8858296871185303,
|
| 436 |
+
"learning_rate": 0.0002015421505577756,
|
| 437 |
+
"loss": 0.5183939933776855,
|
| 438 |
+
"mean_token_accuracy": 0.850081592034071,
|
| 439 |
+
"num_tokens": 980589.0,
|
| 440 |
+
"step": 420
|
| 441 |
+
},
|
| 442 |
+
{
|
| 443 |
+
"epoch": 1.0448318804483188,
|
| 444 |
+
"eval_entropy": 0.5583065545489622,
|
| 445 |
+
"eval_loss": 0.5605642199516296,
|
| 446 |
+
"eval_mean_token_accuracy": 0.8439708411000496,
|
| 447 |
+
"eval_num_tokens": 980589.0,
|
| 448 |
+
"eval_runtime": 86.5422,
|
| 449 |
+
"eval_samples_per_second": 15.9,
|
| 450 |
+
"eval_steps_per_second": 1.987,
|
| 451 |
+
"step": 420
|
| 452 |
+
},
|
| 453 |
+
{
|
| 454 |
+
"entropy": 0.5671238023787737,
|
| 455 |
+
"epoch": 1.0946450809464507,
|
| 456 |
+
"grad_norm": 0.6882498264312744,
|
| 457 |
+
"learning_rate": 0.00020150112347025443,
|
| 458 |
+
"loss": 0.5077326774597168,
|
| 459 |
+
"mean_token_accuracy": 0.8489868573844432,
|
| 460 |
+
"num_tokens": 1027852.0,
|
| 461 |
+
"step": 440
|
| 462 |
+
},
|
| 463 |
+
{
|
| 464 |
+
"epoch": 1.0946450809464507,
|
| 465 |
+
"eval_entropy": 0.5868900277933409,
|
| 466 |
+
"eval_loss": 0.5602695345878601,
|
| 467 |
+
"eval_mean_token_accuracy": 0.8428842161977014,
|
| 468 |
+
"eval_num_tokens": 1027852.0,
|
| 469 |
+
"eval_runtime": 86.623,
|
| 470 |
+
"eval_samples_per_second": 15.885,
|
| 471 |
+
"eval_steps_per_second": 1.986,
|
| 472 |
+
"step": 440
|
| 473 |
+
},
|
| 474 |
+
{
|
| 475 |
+
"entropy": 0.5533561781048775,
|
| 476 |
+
"epoch": 1.1444582814445827,
|
| 477 |
+
"grad_norm": 0.7717723250389099,
|
| 478 |
+
"learning_rate": 0.0002014297192297181,
|
| 479 |
+
"loss": 0.4954517364501953,
|
| 480 |
+
"mean_token_accuracy": 0.8529035650193691,
|
| 481 |
+
"num_tokens": 1077649.0,
|
| 482 |
+
"step": 460
|
| 483 |
+
},
|
| 484 |
+
{
|
| 485 |
+
"epoch": 1.1444582814445827,
|
| 486 |
+
"eval_entropy": 0.5600803743961246,
|
| 487 |
+
"eval_loss": 0.5608077645301819,
|
| 488 |
+
"eval_mean_token_accuracy": 0.8445036771685578,
|
| 489 |
+
"eval_num_tokens": 1077649.0,
|
| 490 |
+
"eval_runtime": 86.1316,
|
| 491 |
+
"eval_samples_per_second": 15.976,
|
| 492 |
+
"eval_steps_per_second": 1.997,
|
| 493 |
+
"step": 460
|
| 494 |
+
},
|
| 495 |
+
{
|
| 496 |
+
"entropy": 0.5692154694348573,
|
| 497 |
+
"epoch": 1.1942714819427147,
|
| 498 |
+
"grad_norm": 0.7322827577590942,
|
| 499 |
+
"learning_rate": 0.0002013279593707117,
|
| 500 |
+
"loss": 0.505049467086792,
|
| 501 |
+
"mean_token_accuracy": 0.8551576808094978,
|
| 502 |
+
"num_tokens": 1124872.0,
|
| 503 |
+
"step": 480
|
| 504 |
+
},
|
| 505 |
+
{
|
| 506 |
+
"epoch": 1.1942714819427147,
|
| 507 |
+
"eval_entropy": 0.5732695829383162,
|
| 508 |
+
"eval_loss": 0.5594323873519897,
|
| 509 |
+
"eval_mean_token_accuracy": 0.8449713407560836,
|
| 510 |
+
"eval_num_tokens": 1124872.0,
|
| 511 |
+
"eval_runtime": 86.2726,
|
| 512 |
+
"eval_samples_per_second": 15.949,
|
| 513 |
+
"eval_steps_per_second": 1.994,
|
| 514 |
+
"step": 480
|
| 515 |
+
},
|
| 516 |
+
{
|
| 517 |
+
"entropy": 0.5817618492990733,
|
| 518 |
+
"epoch": 1.244084682440847,
|
| 519 |
+
"grad_norm": 1.1776764392852783,
|
| 520 |
+
"learning_rate": 0.0002011958745826208,
|
| 521 |
+
"loss": 0.5137609958648681,
|
| 522 |
+
"mean_token_accuracy": 0.8521522544324398,
|
| 523 |
+
"num_tokens": 1168698.0,
|
| 524 |
+
"step": 500
|
| 525 |
+
},
|
| 526 |
+
{
|
| 527 |
+
"epoch": 1.244084682440847,
|
| 528 |
+
"eval_entropy": 0.5662581343636957,
|
| 529 |
+
"eval_loss": 0.5595026016235352,
|
| 530 |
+
"eval_mean_token_accuracy": 0.8441977164773053,
|
| 531 |
+
"eval_num_tokens": 1168698.0,
|
| 532 |
+
"eval_runtime": 86.7261,
|
| 533 |
+
"eval_samples_per_second": 15.866,
|
| 534 |
+
"eval_steps_per_second": 1.983,
|
| 535 |
+
"step": 500
|
| 536 |
+
},
|
| 537 |
+
{
|
| 538 |
+
"entropy": 0.5712925456464291,
|
| 539 |
+
"epoch": 1.293897882938979,
|
| 540 |
+
"grad_norm": 0.7960361838340759,
|
| 541 |
+
"learning_rate": 0.0002010335047004159,
|
| 542 |
+
"loss": 0.5134767532348633,
|
| 543 |
+
"mean_token_accuracy": 0.8513577707111836,
|
| 544 |
+
"num_tokens": 1216679.0,
|
| 545 |
+
"step": 520
|
| 546 |
+
},
|
| 547 |
+
{
|
| 548 |
+
"epoch": 1.293897882938979,
|
| 549 |
+
"eval_entropy": 0.5441222797299541,
|
| 550 |
+
"eval_loss": 0.5535460114479065,
|
| 551 |
+
"eval_mean_token_accuracy": 0.8450886118550633,
|
| 552 |
+
"eval_num_tokens": 1216679.0,
|
| 553 |
+
"eval_runtime": 86.2675,
|
| 554 |
+
"eval_samples_per_second": 15.95,
|
| 555 |
+
"eval_steps_per_second": 1.994,
|
| 556 |
+
"step": 520
|
| 557 |
+
},
|
| 558 |
+
{
|
| 559 |
+
"entropy": 0.5787045754492283,
|
| 560 |
+
"epoch": 1.3437110834371109,
|
| 561 |
+
"grad_norm": 0.9205410480499268,
|
| 562 |
+
"learning_rate": 0.00020084089869263887,
|
| 563 |
+
"loss": 0.5119701862335205,
|
| 564 |
+
"mean_token_accuracy": 0.8503516331315041,
|
| 565 |
+
"num_tokens": 1261365.0,
|
| 566 |
+
"step": 540
|
| 567 |
+
},
|
| 568 |
+
{
|
| 569 |
+
"epoch": 1.3437110834371109,
|
| 570 |
+
"eval_entropy": 0.5744457827057949,
|
| 571 |
+
"eval_loss": 0.5514978766441345,
|
| 572 |
+
"eval_mean_token_accuracy": 0.845929987901865,
|
| 573 |
+
"eval_num_tokens": 1261365.0,
|
| 574 |
+
"eval_runtime": 86.2299,
|
| 575 |
+
"eval_samples_per_second": 15.957,
|
| 576 |
+
"eval_steps_per_second": 1.995,
|
| 577 |
+
"step": 540
|
| 578 |
+
},
|
| 579 |
+
{
|
| 580 |
+
"entropy": 0.5739392962306737,
|
| 581 |
+
"epoch": 1.3935242839352429,
|
| 582 |
+
"grad_norm": 0.7475653886795044,
|
| 583 |
+
"learning_rate": 0.00020061811464663464,
|
| 584 |
+
"loss": 0.5189042091369629,
|
| 585 |
+
"mean_token_accuracy": 0.8492388024926185,
|
| 586 |
+
"num_tokens": 1306879.0,
|
| 587 |
+
"step": 560
|
| 588 |
+
},
|
| 589 |
+
{
|
| 590 |
+
"epoch": 1.3935242839352429,
|
| 591 |
+
"eval_entropy": 0.6116398271433142,
|
| 592 |
+
"eval_loss": 0.551732063293457,
|
| 593 |
+
"eval_mean_token_accuracy": 0.8450756967067719,
|
| 594 |
+
"eval_num_tokens": 1306879.0,
|
| 595 |
+
"eval_runtime": 86.6081,
|
| 596 |
+
"eval_samples_per_second": 15.888,
|
| 597 |
+
"eval_steps_per_second": 1.986,
|
| 598 |
+
"step": 560
|
| 599 |
+
},
|
| 600 |
+
{
|
| 601 |
+
"entropy": 0.5755622573196888,
|
| 602 |
+
"epoch": 1.4433374844333748,
|
| 603 |
+
"grad_norm": 0.8218411803245544,
|
| 604 |
+
"learning_rate": 0.00020036521975103286,
|
| 605 |
+
"loss": 0.5106248378753662,
|
| 606 |
+
"mean_token_accuracy": 0.8506785586476326,
|
| 607 |
+
"num_tokens": 1353534.0,
|
| 608 |
+
"step": 580
|
| 609 |
+
},
|
| 610 |
+
{
|
| 611 |
+
"epoch": 1.4433374844333748,
|
| 612 |
+
"eval_entropy": 0.5906928708386976,
|
| 613 |
+
"eval_loss": 0.551278829574585,
|
| 614 |
+
"eval_mean_token_accuracy": 0.8462819308042526,
|
| 615 |
+
"eval_num_tokens": 1353534.0,
|
| 616 |
+
"eval_runtime": 86.5438,
|
| 617 |
+
"eval_samples_per_second": 15.899,
|
| 618 |
+
"eval_steps_per_second": 1.987,
|
| 619 |
+
"step": 580
|
| 620 |
+
},
|
| 621 |
+
{
|
| 622 |
+
"entropy": 0.5694822132587433,
|
| 623 |
+
"epoch": 1.4931506849315068,
|
| 624 |
+
"grad_norm": 0.8880652189254761,
|
| 625 |
+
"learning_rate": 0.00020008229027548475,
|
| 626 |
+
"loss": 0.5140334606170655,
|
| 627 |
+
"mean_token_accuracy": 0.8521522797644139,
|
| 628 |
+
"num_tokens": 1399537.0,
|
| 629 |
+
"step": 600
|
| 630 |
+
},
|
| 631 |
+
{
|
| 632 |
+
"epoch": 1.4931506849315068,
|
| 633 |
+
"eval_entropy": 0.5599641964532608,
|
| 634 |
+
"eval_loss": 0.5501875877380371,
|
| 635 |
+
"eval_mean_token_accuracy": 0.8467660788879838,
|
| 636 |
+
"eval_num_tokens": 1399537.0,
|
| 637 |
+
"eval_runtime": 86.6458,
|
| 638 |
+
"eval_samples_per_second": 15.881,
|
| 639 |
+
"eval_steps_per_second": 1.985,
|
| 640 |
+
"step": 600
|
| 641 |
+
},
|
| 642 |
+
{
|
| 643 |
+
"entropy": 0.5675108034163714,
|
| 644 |
+
"epoch": 1.5429638854296388,
|
| 645 |
+
"grad_norm": 0.837087094783783,
|
| 646 |
+
"learning_rate": 0.0001997694115476612,
|
| 647 |
+
"loss": 0.5099846363067627,
|
| 648 |
+
"mean_token_accuracy": 0.8543680295348167,
|
| 649 |
+
"num_tokens": 1448422.0,
|
| 650 |
+
"step": 620
|
| 651 |
+
},
|
| 652 |
+
{
|
| 653 |
+
"epoch": 1.5429638854296388,
|
| 654 |
+
"eval_entropy": 0.5728072581249614,
|
| 655 |
+
"eval_loss": 0.5445425510406494,
|
| 656 |
+
"eval_mean_token_accuracy": 0.8474342175001321,
|
| 657 |
+
"eval_num_tokens": 1448422.0,
|
| 658 |
+
"eval_runtime": 86.4859,
|
| 659 |
+
"eval_samples_per_second": 15.91,
|
| 660 |
+
"eval_steps_per_second": 1.989,
|
| 661 |
+
"step": 620
|
| 662 |
+
},
|
| 663 |
+
{
|
| 664 |
+
"entropy": 0.5700885068625212,
|
| 665 |
+
"epoch": 1.592777085927771,
|
| 666 |
+
"grad_norm": 0.6598765850067139,
|
| 667 |
+
"learning_rate": 0.000199426677927519,
|
| 668 |
+
"loss": 0.5122694969177246,
|
| 669 |
+
"mean_token_accuracy": 0.8519927568733692,
|
| 670 |
+
"num_tokens": 1495009.0,
|
| 671 |
+
"step": 640
|
| 672 |
+
},
|
| 673 |
+
{
|
| 674 |
+
"epoch": 1.592777085927771,
|
| 675 |
+
"eval_entropy": 0.5476993622128353,
|
| 676 |
+
"eval_loss": 0.5427973866462708,
|
| 677 |
+
"eval_mean_token_accuracy": 0.8478512147138285,
|
| 678 |
+
"eval_num_tokens": 1495009.0,
|
| 679 |
+
"eval_runtime": 86.4172,
|
| 680 |
+
"eval_samples_per_second": 15.923,
|
| 681 |
+
"eval_steps_per_second": 1.99,
|
| 682 |
+
"step": 640
|
| 683 |
+
},
|
| 684 |
+
{
|
| 685 |
+
"entropy": 0.5829229176044464,
|
| 686 |
+
"epoch": 1.6425902864259028,
|
| 687 |
+
"grad_norm": 0.6965194940567017,
|
| 688 |
+
"learning_rate": 0.00019905419277884342,
|
| 689 |
+
"loss": 0.5253659725189209,
|
| 690 |
+
"mean_token_accuracy": 0.8493309423327446,
|
| 691 |
+
"num_tokens": 1536932.0,
|
| 692 |
+
"step": 660
|
| 693 |
+
},
|
| 694 |
+
{
|
| 695 |
+
"epoch": 1.6425902864259028,
|
| 696 |
+
"eval_entropy": 0.5666290084983028,
|
| 697 |
+
"eval_loss": 0.5467478036880493,
|
| 698 |
+
"eval_mean_token_accuracy": 0.8479407703460649,
|
| 699 |
+
"eval_num_tokens": 1536932.0,
|
| 700 |
+
"eval_runtime": 86.4414,
|
| 701 |
+
"eval_samples_per_second": 15.918,
|
| 702 |
+
"eval_steps_per_second": 1.99,
|
| 703 |
+
"step": 660
|
| 704 |
+
},
|
| 705 |
+
{
|
| 706 |
+
"entropy": 0.5498311135917902,
|
| 707 |
+
"epoch": 1.692403486924035,
|
| 708 |
+
"grad_norm": 0.636583685874939,
|
| 709 |
+
"learning_rate": 0.00019865206843807482,
|
| 710 |
+
"loss": 0.49981012344360354,
|
| 711 |
+
"mean_token_accuracy": 0.8560848504304885,
|
| 712 |
+
"num_tokens": 1585718.0,
|
| 713 |
+
"step": 680
|
| 714 |
+
},
|
| 715 |
+
{
|
| 716 |
+
"epoch": 1.692403486924035,
|
| 717 |
+
"eval_entropy": 0.539117265406043,
|
| 718 |
+
"eval_loss": 0.53994220495224,
|
| 719 |
+
"eval_mean_token_accuracy": 0.8488582601380903,
|
| 720 |
+
"eval_num_tokens": 1585718.0,
|
| 721 |
+
"eval_runtime": 86.5296,
|
| 722 |
+
"eval_samples_per_second": 15.902,
|
| 723 |
+
"eval_steps_per_second": 1.988,
|
| 724 |
+
"step": 680
|
| 725 |
+
},
|
| 726 |
+
{
|
| 727 |
+
"entropy": 0.5543891470879316,
|
| 728 |
+
"epoch": 1.7422166874221667,
|
| 729 |
+
"grad_norm": 0.6068442463874817,
|
| 730 |
+
"learning_rate": 0.0001982204261804297,
|
| 731 |
+
"loss": 0.498047399520874,
|
| 732 |
+
"mean_token_accuracy": 0.8554679051041603,
|
| 733 |
+
"num_tokens": 1635718.0,
|
| 734 |
+
"step": 700
|
| 735 |
+
},
|
| 736 |
+
{
|
| 737 |
+
"epoch": 1.7422166874221667,
|
| 738 |
+
"eval_entropy": 0.5703774151760478,
|
| 739 |
+
"eval_loss": 0.5300245881080627,
|
| 740 |
+
"eval_mean_token_accuracy": 0.850798153946566,
|
| 741 |
+
"eval_num_tokens": 1635718.0,
|
| 742 |
+
"eval_runtime": 86.6456,
|
| 743 |
+
"eval_samples_per_second": 15.881,
|
| 744 |
+
"eval_steps_per_second": 1.985,
|
| 745 |
+
"step": 700
|
| 746 |
+
},
|
| 747 |
+
{
|
| 748 |
+
"entropy": 0.546524541825056,
|
| 749 |
+
"epoch": 1.792029887920299,
|
| 750 |
+
"grad_norm": 0.7274155020713806,
|
| 751 |
+
"learning_rate": 0.00019775939618332566,
|
| 752 |
+
"loss": 0.4988589286804199,
|
| 753 |
+
"mean_token_accuracy": 0.853422473371029,
|
| 754 |
+
"num_tokens": 1681291.0,
|
| 755 |
+
"step": 720
|
| 756 |
+
},
|
| 757 |
+
{
|
| 758 |
+
"epoch": 1.792029887920299,
|
| 759 |
+
"eval_entropy": 0.5614905688305234,
|
| 760 |
+
"eval_loss": 0.5350332260131836,
|
| 761 |
+
"eval_mean_token_accuracy": 0.8492204359797544,
|
| 762 |
+
"eval_num_tokens": 1681291.0,
|
| 763 |
+
"eval_runtime": 86.7581,
|
| 764 |
+
"eval_samples_per_second": 15.86,
|
| 765 |
+
"eval_steps_per_second": 1.983,
|
| 766 |
+
"step": 720
|
| 767 |
+
},
|
| 768 |
+
{
|
| 769 |
+
"entropy": 0.5519792139530182,
|
| 770 |
+
"epoch": 1.841843088418431,
|
| 771 |
+
"grad_norm": 0.663466215133667,
|
| 772 |
+
"learning_rate": 0.00019726911748712167,
|
| 773 |
+
"loss": 0.5099314212799072,
|
| 774 |
+
"mean_token_accuracy": 0.848412600159645,
|
| 775 |
+
"num_tokens": 1729102.0,
|
| 776 |
+
"step": 740
|
| 777 |
+
},
|
| 778 |
+
{
|
| 779 |
+
"epoch": 1.841843088418431,
|
| 780 |
+
"eval_entropy": 0.5583519090053647,
|
| 781 |
+
"eval_loss": 0.530483603477478,
|
| 782 |
+
"eval_mean_token_accuracy": 0.8500003374593202,
|
| 783 |
+
"eval_num_tokens": 1729102.0,
|
| 784 |
+
"eval_runtime": 86.3961,
|
| 785 |
+
"eval_samples_per_second": 15.927,
|
| 786 |
+
"eval_steps_per_second": 1.991,
|
| 787 |
+
"step": 740
|
| 788 |
+
},
|
| 789 |
+
{
|
| 790 |
+
"entropy": 0.5454779766499996,
|
| 791 |
+
"epoch": 1.891656288916563,
|
| 792 |
+
"grad_norm": 0.890394926071167,
|
| 793 |
+
"learning_rate": 0.00019674973795318548,
|
| 794 |
+
"loss": 0.4931994915008545,
|
| 795 |
+
"mean_token_accuracy": 0.8540832489728928,
|
| 796 |
+
"num_tokens": 1773578.0,
|
| 797 |
+
"step": 760
|
| 798 |
+
},
|
| 799 |
+
{
|
| 800 |
+
"epoch": 1.891656288916563,
|
| 801 |
+
"eval_entropy": 0.572755502406941,
|
| 802 |
+
"eval_loss": 0.5415747761726379,
|
| 803 |
+
"eval_mean_token_accuracy": 0.8444425803284312,
|
| 804 |
+
"eval_num_tokens": 1773578.0,
|
| 805 |
+
"eval_runtime": 86.4323,
|
| 806 |
+
"eval_samples_per_second": 15.92,
|
| 807 |
+
"eval_steps_per_second": 1.99,
|
| 808 |
+
"step": 760
|
| 809 |
+
},
|
| 810 |
+
{
|
| 811 |
+
"entropy": 0.5392089951783419,
|
| 812 |
+
"epoch": 1.9414694894146949,
|
| 813 |
+
"grad_norm": 0.632411777973175,
|
| 814 |
+
"learning_rate": 0.00019620141421930058,
|
| 815 |
+
"loss": 0.4957888603210449,
|
| 816 |
+
"mean_token_accuracy": 0.8549866065382957,
|
| 817 |
+
"num_tokens": 1821725.0,
|
| 818 |
+
"step": 780
|
| 819 |
+
},
|
| 820 |
+
{
|
| 821 |
+
"epoch": 1.9414694894146949,
|
| 822 |
+
"eval_entropy": 0.540764772961306,
|
| 823 |
+
"eval_loss": 0.5327216386795044,
|
| 824 |
+
"eval_mean_token_accuracy": 0.850631088364956,
|
| 825 |
+
"eval_num_tokens": 1821725.0,
|
| 826 |
+
"eval_runtime": 86.8097,
|
| 827 |
+
"eval_samples_per_second": 15.851,
|
| 828 |
+
"eval_steps_per_second": 1.981,
|
| 829 |
+
"step": 780
|
| 830 |
+
},
|
| 831 |
+
{
|
| 832 |
+
"entropy": 0.5674678739160299,
|
| 833 |
+
"epoch": 1.9912826899128269,
|
| 834 |
+
"grad_norm": 0.6958843469619751,
|
| 835 |
+
"learning_rate": 0.0001956243116524263,
|
| 836 |
+
"loss": 0.504389762878418,
|
| 837 |
+
"mean_token_accuracy": 0.8527948908507824,
|
| 838 |
+
"num_tokens": 1868431.0,
|
| 839 |
+
"step": 800
|
| 840 |
+
},
|
| 841 |
+
{
|
| 842 |
+
"epoch": 1.9912826899128269,
|
| 843 |
+
"eval_entropy": 0.530262403190136,
|
| 844 |
+
"eval_loss": 0.5308871865272522,
|
| 845 |
+
"eval_mean_token_accuracy": 0.8522498046242913,
|
| 846 |
+
"eval_num_tokens": 1868431.0,
|
| 847 |
+
"eval_runtime": 86.7942,
|
| 848 |
+
"eval_samples_per_second": 15.854,
|
| 849 |
+
"eval_steps_per_second": 1.982,
|
| 850 |
+
"step": 800
|
| 851 |
+
},
|
| 852 |
+
{
|
| 853 |
+
"entropy": 0.4742849511213792,
|
| 854 |
+
"epoch": 2.0398505603985058,
|
| 855 |
+
"grad_norm": 0.6941492557525635,
|
| 856 |
+
"learning_rate": 0.00019501860429882556,
|
| 857 |
+
"loss": 0.418599271774292,
|
| 858 |
+
"mean_token_accuracy": 0.8748210859604371,
|
| 859 |
+
"num_tokens": 1915280.0,
|
| 860 |
+
"step": 820
|
| 861 |
+
},
|
| 862 |
+
{
|
| 863 |
+
"epoch": 2.0398505603985058,
|
| 864 |
+
"eval_entropy": 0.504602165069691,
|
| 865 |
+
"eval_loss": 0.542878270149231,
|
| 866 |
+
"eval_mean_token_accuracy": 0.8507604484641275,
|
| 867 |
+
"eval_num_tokens": 1915280.0,
|
| 868 |
+
"eval_runtime": 86.7841,
|
| 869 |
+
"eval_samples_per_second": 15.855,
|
| 870 |
+
"eval_steps_per_second": 1.982,
|
| 871 |
+
"step": 820
|
| 872 |
+
},
|
| 873 |
+
{
|
| 874 |
+
"entropy": 0.45857742577791216,
|
| 875 |
+
"epoch": 2.0896637608966375,
|
| 876 |
+
"grad_norm": 0.5791997909545898,
|
| 877 |
+
"learning_rate": 0.00019438447483157478,
|
| 878 |
+
"loss": 0.399777889251709,
|
| 879 |
+
"mean_token_accuracy": 0.8754058346152306,
|
| 880 |
+
"num_tokens": 1965306.0,
|
| 881 |
+
"step": 840
|
| 882 |
+
},
|
| 883 |
+
{
|
| 884 |
+
"epoch": 2.0896637608966375,
|
| 885 |
+
"eval_entropy": 0.5028848362176918,
|
| 886 |
+
"eval_loss": 0.5356478095054626,
|
| 887 |
+
"eval_mean_token_accuracy": 0.8525635412959165,
|
| 888 |
+
"eval_num_tokens": 1965306.0,
|
| 889 |
+
"eval_runtime": 86.6707,
|
| 890 |
+
"eval_samples_per_second": 15.876,
|
| 891 |
+
"eval_steps_per_second": 1.985,
|
| 892 |
+
"step": 840
|
| 893 |
+
},
|
| 894 |
+
{
|
| 895 |
+
"entropy": 0.4869446292519569,
|
| 896 |
+
"epoch": 2.1394769613947697,
|
| 897 |
+
"grad_norm": 0.6483516693115234,
|
| 898 |
+
"learning_rate": 0.00019372211449547223,
|
| 899 |
+
"loss": 0.40715818405151366,
|
| 900 |
+
"mean_token_accuracy": 0.875113020837307,
|
| 901 |
+
"num_tokens": 2008562.0,
|
| 902 |
+
"step": 860
|
| 903 |
+
},
|
| 904 |
+
{
|
| 905 |
+
"epoch": 2.1394769613947697,
|
| 906 |
+
"eval_entropy": 0.4928991326759028,
|
| 907 |
+
"eval_loss": 0.5419561862945557,
|
| 908 |
+
"eval_mean_token_accuracy": 0.8516040146350861,
|
| 909 |
+
"eval_num_tokens": 2008562.0,
|
| 910 |
+
"eval_runtime": 87.0686,
|
| 911 |
+
"eval_samples_per_second": 15.804,
|
| 912 |
+
"eval_steps_per_second": 1.975,
|
| 913 |
+
"step": 860
|
| 914 |
+
},
|
| 915 |
+
{
|
| 916 |
+
"entropy": 0.45819590501487256,
|
| 917 |
+
"epoch": 2.1892901618929015,
|
| 918 |
+
"grad_norm": 0.6661920547485352,
|
| 919 |
+
"learning_rate": 0.00019303172304936108,
|
| 920 |
+
"loss": 0.39511430263519287,
|
| 921 |
+
"mean_token_accuracy": 0.8780680045485496,
|
| 922 |
+
"num_tokens": 2056474.0,
|
| 923 |
+
"step": 880
|
| 924 |
+
},
|
| 925 |
+
{
|
| 926 |
+
"epoch": 2.1892901618929015,
|
| 927 |
+
"eval_entropy": 0.48602560647698334,
|
| 928 |
+
"eval_loss": 0.5436084866523743,
|
| 929 |
+
"eval_mean_token_accuracy": 0.8500938470973525,
|
| 930 |
+
"eval_num_tokens": 2056474.0,
|
| 931 |
+
"eval_runtime": 86.6809,
|
| 932 |
+
"eval_samples_per_second": 15.874,
|
| 933 |
+
"eval_steps_per_second": 1.984,
|
| 934 |
+
"step": 880
|
| 935 |
+
},
|
| 936 |
+
{
|
| 937 |
+
"entropy": 0.4780638810247183,
|
| 938 |
+
"epoch": 2.2391033623910337,
|
| 939 |
+
"grad_norm": 0.6870484352111816,
|
| 940 |
+
"learning_rate": 0.0001923135087058851,
|
| 941 |
+
"loss": 0.4061615467071533,
|
| 942 |
+
"mean_token_accuracy": 0.8766494184732437,
|
| 943 |
+
"num_tokens": 2103543.0,
|
| 944 |
+
"step": 900
|
| 945 |
+
},
|
| 946 |
+
{
|
| 947 |
+
"epoch": 2.2391033623910337,
|
| 948 |
+
"eval_entropy": 0.48236206035281337,
|
| 949 |
+
"eval_loss": 0.5446090698242188,
|
| 950 |
+
"eval_mean_token_accuracy": 0.8507725513258646,
|
| 951 |
+
"eval_num_tokens": 2103543.0,
|
| 952 |
+
"eval_runtime": 86.7398,
|
| 953 |
+
"eval_samples_per_second": 15.864,
|
| 954 |
+
"eval_steps_per_second": 1.983,
|
| 955 |
+
"step": 900
|
| 956 |
+
},
|
| 957 |
+
{
|
| 958 |
+
"entropy": 0.463029869645834,
|
| 959 |
+
"epoch": 2.2889165628891655,
|
| 960 |
+
"grad_norm": 0.6894590854644775,
|
| 961 |
+
"learning_rate": 0.00019156768806869427,
|
| 962 |
+
"loss": 0.39602413177490237,
|
| 963 |
+
"mean_token_accuracy": 0.876420046389103,
|
| 964 |
+
"num_tokens": 2147861.0,
|
| 965 |
+
"step": 920
|
| 966 |
+
},
|
| 967 |
+
{
|
| 968 |
+
"epoch": 2.2889165628891655,
|
| 969 |
+
"eval_entropy": 0.4904779093556626,
|
| 970 |
+
"eval_loss": 0.5404934287071228,
|
| 971 |
+
"eval_mean_token_accuracy": 0.852238280828609,
|
| 972 |
+
"eval_num_tokens": 2147861.0,
|
| 973 |
+
"eval_runtime": 86.5348,
|
| 974 |
+
"eval_samples_per_second": 15.901,
|
| 975 |
+
"eval_steps_per_second": 1.988,
|
| 976 |
+
"step": 920
|
| 977 |
+
},
|
| 978 |
+
{
|
| 979 |
+
"entropy": 0.4817025110125542,
|
| 980 |
+
"epoch": 2.3387297633872977,
|
| 981 |
+
"grad_norm": 0.7756227254867554,
|
| 982 |
+
"learning_rate": 0.00019079448606712033,
|
| 983 |
+
"loss": 0.4177968502044678,
|
| 984 |
+
"mean_token_accuracy": 0.8712256088852882,
|
| 985 |
+
"num_tokens": 2190561.0,
|
| 986 |
+
"step": 940
|
| 987 |
+
},
|
| 988 |
+
{
|
| 989 |
+
"epoch": 2.3387297633872977,
|
| 990 |
+
"eval_entropy": 0.5153802815218305,
|
| 991 |
+
"eval_loss": 0.5424937605857849,
|
| 992 |
+
"eval_mean_token_accuracy": 0.8506565759348315,
|
| 993 |
+
"eval_num_tokens": 2190561.0,
|
| 994 |
+
"eval_runtime": 86.8973,
|
| 995 |
+
"eval_samples_per_second": 15.835,
|
| 996 |
+
"eval_steps_per_second": 1.979,
|
| 997 |
+
"step": 940
|
| 998 |
+
},
|
| 999 |
+
{
|
| 1000 |
+
"entropy": 0.46456389091908934,
|
| 1001 |
+
"epoch": 2.3885429638854294,
|
| 1002 |
+
"grad_norm": 1.2000319957733154,
|
| 1003 |
+
"learning_rate": 0.00018999413588834105,
|
| 1004 |
+
"loss": 0.4084665775299072,
|
| 1005 |
+
"mean_token_accuracy": 0.8750658087432385,
|
| 1006 |
+
"num_tokens": 2239412.0,
|
| 1007 |
+
"step": 960
|
| 1008 |
+
},
|
| 1009 |
+
{
|
| 1010 |
+
"epoch": 2.3885429638854294,
|
| 1011 |
+
"eval_entropy": 0.4849439303195754,
|
| 1012 |
+
"eval_loss": 0.545662522315979,
|
| 1013 |
+
"eval_mean_token_accuracy": 0.8491013112456299,
|
| 1014 |
+
"eval_num_tokens": 2239412.0,
|
| 1015 |
+
"eval_runtime": 86.9049,
|
| 1016 |
+
"eval_samples_per_second": 15.833,
|
| 1017 |
+
"eval_steps_per_second": 1.979,
|
| 1018 |
+
"step": 960
|
| 1019 |
+
},
|
| 1020 |
+
{
|
| 1021 |
+
"entropy": 0.4857471022754908,
|
| 1022 |
+
"epoch": 2.4383561643835616,
|
| 1023 |
+
"grad_norm": 0.9696341753005981,
|
| 1024 |
+
"learning_rate": 0.0001891668789070541,
|
| 1025 |
+
"loss": 0.4149796962738037,
|
| 1026 |
+
"mean_token_accuracy": 0.8704176343977451,
|
| 1027 |
+
"num_tokens": 2286283.0,
|
| 1028 |
+
"step": 980
|
| 1029 |
+
},
|
| 1030 |
+
{
|
| 1031 |
+
"epoch": 2.4383561643835616,
|
| 1032 |
+
"eval_entropy": 0.4872790058684904,
|
| 1033 |
+
"eval_loss": 0.5412707924842834,
|
| 1034 |
+
"eval_mean_token_accuracy": 0.8509329602468846,
|
| 1035 |
+
"eval_num_tokens": 2286283.0,
|
| 1036 |
+
"eval_runtime": 86.7846,
|
| 1037 |
+
"eval_samples_per_second": 15.855,
|
| 1038 |
+
"eval_steps_per_second": 1.982,
|
| 1039 |
+
"step": 980
|
| 1040 |
+
},
|
| 1041 |
+
{
|
| 1042 |
+
"entropy": 0.4727417893707752,
|
| 1043 |
+
"epoch": 2.488169364881694,
|
| 1044 |
+
"grad_norm": 0.7852500677108765,
|
| 1045 |
+
"learning_rate": 0.0001883129646126818,
|
| 1046 |
+
"loss": 0.4142886161804199,
|
| 1047 |
+
"mean_token_accuracy": 0.8712429471313954,
|
| 1048 |
+
"num_tokens": 2333733.0,
|
| 1049 |
+
"step": 1000
|
| 1050 |
+
},
|
| 1051 |
+
{
|
| 1052 |
+
"epoch": 2.488169364881694,
|
| 1053 |
+
"eval_entropy": 0.5386548059624295,
|
| 1054 |
+
"eval_loss": 0.536101222038269,
|
| 1055 |
+
"eval_mean_token_accuracy": 0.8499491239009902,
|
| 1056 |
+
"eval_num_tokens": 2333733.0,
|
| 1057 |
+
"eval_runtime": 86.9501,
|
| 1058 |
+
"eval_samples_per_second": 15.825,
|
| 1059 |
+
"eval_steps_per_second": 1.978,
|
| 1060 |
+
"step": 1000
|
| 1061 |
+
},
|
| 1062 |
+
{
|
| 1063 |
+
"entropy": 0.4673406321555376,
|
| 1064 |
+
"epoch": 2.5379825653798256,
|
| 1065 |
+
"grad_norm": 0.7133921384811401,
|
| 1066 |
+
"learning_rate": 0.0001874326505341286,
|
| 1067 |
+
"loss": 0.40857529640197754,
|
| 1068 |
+
"mean_token_accuracy": 0.8747925907373428,
|
| 1069 |
+
"num_tokens": 2384270.0,
|
| 1070 |
+
"step": 1020
|
| 1071 |
+
},
|
| 1072 |
+
{
|
| 1073 |
+
"epoch": 2.5379825653798256,
|
| 1074 |
+
"eval_entropy": 0.495788364909416,
|
| 1075 |
+
"eval_loss": 0.5418923497200012,
|
| 1076 |
+
"eval_mean_token_accuracy": 0.851321972040243,
|
| 1077 |
+
"eval_num_tokens": 2384270.0,
|
| 1078 |
+
"eval_runtime": 86.7154,
|
| 1079 |
+
"eval_samples_per_second": 15.868,
|
| 1080 |
+
"eval_steps_per_second": 1.983,
|
| 1081 |
+
"step": 1020
|
| 1082 |
+
},
|
| 1083 |
+
{
|
| 1084 |
+
"entropy": 0.47599745728075504,
|
| 1085 |
+
"epoch": 2.587795765877958,
|
| 1086 |
+
"grad_norm": 0.8202953338623047,
|
| 1087 |
+
"learning_rate": 0.0001865262021621137,
|
| 1088 |
+
"loss": 0.40998234748840334,
|
| 1089 |
+
"mean_token_accuracy": 0.8758242674171924,
|
| 1090 |
+
"num_tokens": 2428036.0,
|
| 1091 |
+
"step": 1040
|
| 1092 |
+
},
|
| 1093 |
+
{
|
| 1094 |
+
"epoch": 2.587795765877958,
|
| 1095 |
+
"eval_entropy": 0.4887966953737791,
|
| 1096 |
+
"eval_loss": 0.5408804416656494,
|
| 1097 |
+
"eval_mean_token_accuracy": 0.8512661065473113,
|
| 1098 |
+
"eval_num_tokens": 2428036.0,
|
| 1099 |
+
"eval_runtime": 86.7869,
|
| 1100 |
+
"eval_samples_per_second": 15.855,
|
| 1101 |
+
"eval_steps_per_second": 1.982,
|
| 1102 |
+
"step": 1040
|
| 1103 |
+
}
|
| 1104 |
+
],
|
| 1105 |
+
"logging_steps": 20,
|
| 1106 |
+
"max_steps": 4020,
|
| 1107 |
+
"num_input_tokens_seen": 0,
|
| 1108 |
+
"num_train_epochs": 10,
|
| 1109 |
+
"save_steps": 20,
|
| 1110 |
+
"stateful_callbacks": {
|
| 1111 |
+
"TrainerControl": {
|
| 1112 |
+
"args": {
|
| 1113 |
+
"should_epoch_stop": false,
|
| 1114 |
+
"should_evaluate": false,
|
| 1115 |
+
"should_log": false,
|
| 1116 |
+
"should_save": true,
|
| 1117 |
+
"should_training_stop": false
|
| 1118 |
+
},
|
| 1119 |
+
"attributes": {}
|
| 1120 |
+
}
|
| 1121 |
+
},
|
| 1122 |
+
"total_flos": 1.0254458345271091e+17,
|
| 1123 |
+
"train_batch_size": 4,
|
| 1124 |
+
"trial_name": null,
|
| 1125 |
+
"trial_params": null
|
| 1126 |
+
}
|
overgeneralisation_original_Swedish/Qwen3.5-4B-Base_overgeneralisation_splits_original_features_train_overgeneralisation_splits_original_features_test1/checkpoint-1060/README.md
ADDED
|
@@ -0,0 +1,209 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
---
|
| 2 |
+
base_model: Qwen/Qwen3.5-4B-Base
|
| 3 |
+
library_name: peft
|
| 4 |
+
pipeline_tag: text-generation
|
| 5 |
+
tags:
|
| 6 |
+
- base_model:adapter:Qwen/Qwen3.5-4B-Base
|
| 7 |
+
- lora
|
| 8 |
+
- sft
|
| 9 |
+
- transformers
|
| 10 |
+
- trl
|
| 11 |
+
---
|
| 12 |
+
|
| 13 |
+
# Model Card for Model ID
|
| 14 |
+
|
| 15 |
+
<!-- Provide a quick summary of what the model is/does. -->
|
| 16 |
+
|
| 17 |
+
|
| 18 |
+
|
| 19 |
+
## Model Details
|
| 20 |
+
|
| 21 |
+
### Model Description
|
| 22 |
+
|
| 23 |
+
<!-- Provide a longer summary of what this model is. -->
|
| 24 |
+
|
| 25 |
+
|
| 26 |
+
|
| 27 |
+
- **Developed by:** [More Information Needed]
|
| 28 |
+
- **Funded by [optional]:** [More Information Needed]
|
| 29 |
+
- **Shared by [optional]:** [More Information Needed]
|
| 30 |
+
- **Model type:** [More Information Needed]
|
| 31 |
+
- **Language(s) (NLP):** [More Information Needed]
|
| 32 |
+
- **License:** [More Information Needed]
|
| 33 |
+
- **Finetuned from model [optional]:** [More Information Needed]
|
| 34 |
+
|
| 35 |
+
### Model Sources [optional]
|
| 36 |
+
|
| 37 |
+
<!-- Provide the basic links for the model. -->
|
| 38 |
+
|
| 39 |
+
- **Repository:** [More Information Needed]
|
| 40 |
+
- **Paper [optional]:** [More Information Needed]
|
| 41 |
+
- **Demo [optional]:** [More Information Needed]
|
| 42 |
+
|
| 43 |
+
## Uses
|
| 44 |
+
|
| 45 |
+
<!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
|
| 46 |
+
|
| 47 |
+
### Direct Use
|
| 48 |
+
|
| 49 |
+
<!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
|
| 50 |
+
|
| 51 |
+
[More Information Needed]
|
| 52 |
+
|
| 53 |
+
### Downstream Use [optional]
|
| 54 |
+
|
| 55 |
+
<!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
|
| 56 |
+
|
| 57 |
+
[More Information Needed]
|
| 58 |
+
|
| 59 |
+
### Out-of-Scope Use
|
| 60 |
+
|
| 61 |
+
<!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
|
| 62 |
+
|
| 63 |
+
[More Information Needed]
|
| 64 |
+
|
| 65 |
+
## Bias, Risks, and Limitations
|
| 66 |
+
|
| 67 |
+
<!-- This section is meant to convey both technical and sociotechnical limitations. -->
|
| 68 |
+
|
| 69 |
+
[More Information Needed]
|
| 70 |
+
|
| 71 |
+
### Recommendations
|
| 72 |
+
|
| 73 |
+
<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
|
| 74 |
+
|
| 75 |
+
Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
|
| 76 |
+
|
| 77 |
+
## How to Get Started with the Model
|
| 78 |
+
|
| 79 |
+
Use the code below to get started with the model.
|
| 80 |
+
|
| 81 |
+
[More Information Needed]
|
| 82 |
+
|
| 83 |
+
## Training Details
|
| 84 |
+
|
| 85 |
+
### Training Data
|
| 86 |
+
|
| 87 |
+
<!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
|
| 88 |
+
|
| 89 |
+
[More Information Needed]
|
| 90 |
+
|
| 91 |
+
### Training Procedure
|
| 92 |
+
|
| 93 |
+
<!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
|
| 94 |
+
|
| 95 |
+
#### Preprocessing [optional]
|
| 96 |
+
|
| 97 |
+
[More Information Needed]
|
| 98 |
+
|
| 99 |
+
|
| 100 |
+
#### Training Hyperparameters
|
| 101 |
+
|
| 102 |
+
- **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
|
| 103 |
+
|
| 104 |
+
#### Speeds, Sizes, Times [optional]
|
| 105 |
+
|
| 106 |
+
<!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
|
| 107 |
+
|
| 108 |
+
[More Information Needed]
|
| 109 |
+
|
| 110 |
+
## Evaluation
|
| 111 |
+
|
| 112 |
+
<!-- This section describes the evaluation protocols and provides the results. -->
|
| 113 |
+
|
| 114 |
+
### Testing Data, Factors & Metrics
|
| 115 |
+
|
| 116 |
+
#### Testing Data
|
| 117 |
+
|
| 118 |
+
<!-- This should link to a Dataset Card if possible. -->
|
| 119 |
+
|
| 120 |
+
[More Information Needed]
|
| 121 |
+
|
| 122 |
+
#### Factors
|
| 123 |
+
|
| 124 |
+
<!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
|
| 125 |
+
|
| 126 |
+
[More Information Needed]
|
| 127 |
+
|
| 128 |
+
#### Metrics
|
| 129 |
+
|
| 130 |
+
<!-- These are the evaluation metrics being used, ideally with a description of why. -->
|
| 131 |
+
|
| 132 |
+
[More Information Needed]
|
| 133 |
+
|
| 134 |
+
### Results
|
| 135 |
+
|
| 136 |
+
[More Information Needed]
|
| 137 |
+
|
| 138 |
+
#### Summary
|
| 139 |
+
|
| 140 |
+
|
| 141 |
+
|
| 142 |
+
## Model Examination [optional]
|
| 143 |
+
|
| 144 |
+
<!-- Relevant interpretability work for the model goes here -->
|
| 145 |
+
|
| 146 |
+
[More Information Needed]
|
| 147 |
+
|
| 148 |
+
## Environmental Impact
|
| 149 |
+
|
| 150 |
+
<!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
|
| 151 |
+
|
| 152 |
+
Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
|
| 153 |
+
|
| 154 |
+
- **Hardware Type:** [More Information Needed]
|
| 155 |
+
- **Hours used:** [More Information Needed]
|
| 156 |
+
- **Cloud Provider:** [More Information Needed]
|
| 157 |
+
- **Compute Region:** [More Information Needed]
|
| 158 |
+
- **Carbon Emitted:** [More Information Needed]
|
| 159 |
+
|
| 160 |
+
## Technical Specifications [optional]
|
| 161 |
+
|
| 162 |
+
### Model Architecture and Objective
|
| 163 |
+
|
| 164 |
+
[More Information Needed]
|
| 165 |
+
|
| 166 |
+
### Compute Infrastructure
|
| 167 |
+
|
| 168 |
+
[More Information Needed]
|
| 169 |
+
|
| 170 |
+
#### Hardware
|
| 171 |
+
|
| 172 |
+
[More Information Needed]
|
| 173 |
+
|
| 174 |
+
#### Software
|
| 175 |
+
|
| 176 |
+
[More Information Needed]
|
| 177 |
+
|
| 178 |
+
## Citation [optional]
|
| 179 |
+
|
| 180 |
+
<!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
|
| 181 |
+
|
| 182 |
+
**BibTeX:**
|
| 183 |
+
|
| 184 |
+
[More Information Needed]
|
| 185 |
+
|
| 186 |
+
**APA:**
|
| 187 |
+
|
| 188 |
+
[More Information Needed]
|
| 189 |
+
|
| 190 |
+
## Glossary [optional]
|
| 191 |
+
|
| 192 |
+
<!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
|
| 193 |
+
|
| 194 |
+
[More Information Needed]
|
| 195 |
+
|
| 196 |
+
## More Information [optional]
|
| 197 |
+
|
| 198 |
+
[More Information Needed]
|
| 199 |
+
|
| 200 |
+
## Model Card Authors [optional]
|
| 201 |
+
|
| 202 |
+
[More Information Needed]
|
| 203 |
+
|
| 204 |
+
## Model Card Contact
|
| 205 |
+
|
| 206 |
+
[More Information Needed]
|
| 207 |
+
### Framework versions
|
| 208 |
+
|
| 209 |
+
- PEFT 0.18.1
|
overgeneralisation_original_Swedish/Qwen3.5-4B-Base_overgeneralisation_splits_original_features_train_overgeneralisation_splits_original_features_test1/checkpoint-1060/adapter_config.json
ADDED
|
@@ -0,0 +1,46 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
{
|
| 2 |
+
"alora_invocation_tokens": null,
|
| 3 |
+
"alpha_pattern": {},
|
| 4 |
+
"arrow_config": null,
|
| 5 |
+
"auto_mapping": null,
|
| 6 |
+
"base_model_name_or_path": "Qwen/Qwen3.5-4B-Base",
|
| 7 |
+
"bias": "none",
|
| 8 |
+
"corda_config": null,
|
| 9 |
+
"ensure_weight_tying": false,
|
| 10 |
+
"eva_config": null,
|
| 11 |
+
"exclude_modules": null,
|
| 12 |
+
"fan_in_fan_out": false,
|
| 13 |
+
"inference_mode": true,
|
| 14 |
+
"init_lora_weights": true,
|
| 15 |
+
"layer_replication": null,
|
| 16 |
+
"layers_pattern": null,
|
| 17 |
+
"layers_to_transform": null,
|
| 18 |
+
"loftq_config": {},
|
| 19 |
+
"lora_alpha": 256,
|
| 20 |
+
"lora_bias": false,
|
| 21 |
+
"lora_dropout": 0.0005183818805460705,
|
| 22 |
+
"megatron_config": null,
|
| 23 |
+
"megatron_core": "megatron.core",
|
| 24 |
+
"modules_to_save": null,
|
| 25 |
+
"peft_type": "LORA",
|
| 26 |
+
"peft_version": "0.18.1",
|
| 27 |
+
"qalora_group_size": 16,
|
| 28 |
+
"r": 128,
|
| 29 |
+
"rank_pattern": {},
|
| 30 |
+
"revision": null,
|
| 31 |
+
"target_modules": [
|
| 32 |
+
"up_proj",
|
| 33 |
+
"q_proj",
|
| 34 |
+
"o_proj",
|
| 35 |
+
"v_proj",
|
| 36 |
+
"k_proj",
|
| 37 |
+
"gate_proj",
|
| 38 |
+
"down_proj"
|
| 39 |
+
],
|
| 40 |
+
"target_parameters": null,
|
| 41 |
+
"task_type": "CAUSAL_LM",
|
| 42 |
+
"trainable_token_indices": null,
|
| 43 |
+
"use_dora": false,
|
| 44 |
+
"use_qalora": false,
|
| 45 |
+
"use_rslora": false
|
| 46 |
+
}
|
overgeneralisation_original_Swedish/Qwen3.5-4B-Base_overgeneralisation_splits_original_features_train_overgeneralisation_splits_original_features_test1/checkpoint-1060/chat_template.jinja
ADDED
|
@@ -0,0 +1,154 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
{%- set image_count = namespace(value=0) %}
|
| 2 |
+
{%- set video_count = namespace(value=0) %}
|
| 3 |
+
{%- macro render_content(content, do_vision_count, is_system_content=false) %}
|
| 4 |
+
{%- if content is string %}
|
| 5 |
+
{{- content }}
|
| 6 |
+
{%- elif content is iterable and content is not mapping %}
|
| 7 |
+
{%- for item in content %}
|
| 8 |
+
{%- if 'image' in item or 'image_url' in item or item.type == 'image' %}
|
| 9 |
+
{%- if is_system_content %}
|
| 10 |
+
{{- raise_exception('System message cannot contain images.') }}
|
| 11 |
+
{%- endif %}
|
| 12 |
+
{%- if do_vision_count %}
|
| 13 |
+
{%- set image_count.value = image_count.value + 1 %}
|
| 14 |
+
{%- endif %}
|
| 15 |
+
{%- if add_vision_id %}
|
| 16 |
+
{{- 'Picture ' ~ image_count.value ~ ': ' }}
|
| 17 |
+
{%- endif %}
|
| 18 |
+
{{- '<|vision_start|><|image_pad|><|vision_end|>' }}
|
| 19 |
+
{%- elif 'video' in item or item.type == 'video' %}
|
| 20 |
+
{%- if is_system_content %}
|
| 21 |
+
{{- raise_exception('System message cannot contain videos.') }}
|
| 22 |
+
{%- endif %}
|
| 23 |
+
{%- if do_vision_count %}
|
| 24 |
+
{%- set video_count.value = video_count.value + 1 %}
|
| 25 |
+
{%- endif %}
|
| 26 |
+
{%- if add_vision_id %}
|
| 27 |
+
{{- 'Video ' ~ video_count.value ~ ': ' }}
|
| 28 |
+
{%- endif %}
|
| 29 |
+
{{- '<|vision_start|><|video_pad|><|vision_end|>' }}
|
| 30 |
+
{%- elif 'text' in item %}
|
| 31 |
+
{{- item.text }}
|
| 32 |
+
{%- else %}
|
| 33 |
+
{{- raise_exception('Unexpected item type in content.') }}
|
| 34 |
+
{%- endif %}
|
| 35 |
+
{%- endfor %}
|
| 36 |
+
{%- elif content is none or content is undefined %}
|
| 37 |
+
{{- '' }}
|
| 38 |
+
{%- else %}
|
| 39 |
+
{{- raise_exception('Unexpected content type.') }}
|
| 40 |
+
{%- endif %}
|
| 41 |
+
{%- endmacro %}
|
| 42 |
+
{%- if not messages %}
|
| 43 |
+
{{- raise_exception('No messages provided.') }}
|
| 44 |
+
{%- endif %}
|
| 45 |
+
{%- if tools and tools is iterable and tools is not mapping %}
|
| 46 |
+
{{- '<|im_start|>system\n' }}
|
| 47 |
+
{{- "# Tools\n\nYou have access to the following functions:\n\n<tools>" }}
|
| 48 |
+
{%- for tool in tools %}
|
| 49 |
+
{{- "\n" }}
|
| 50 |
+
{{- tool | tojson }}
|
| 51 |
+
{%- endfor %}
|
| 52 |
+
{{- "\n</tools>" }}
|
| 53 |
+
{{- '\n\nIf you choose to call a function ONLY reply in the following format with NO suffix:\n\n<tool_call>\n<function=example_function_name>\n<parameter=example_parameter_1>\nvalue_1\n</parameter>\n<parameter=example_parameter_2>\nThis is the value for the second parameter\nthat can span\nmultiple lines\n</parameter>\n</function>\n</tool_call>\n\n<IMPORTANT>\nReminder:\n- Function calls MUST follow the specified format: an inner <function=...></function> block must be nested within <tool_call></tool_call> XML tags\n- Required parameters MUST be specified\n- You may provide optional reasoning for your function call in natural language BEFORE the function call, but NOT after\n- If there is no function call available, answer the question like normal with your current knowledge and do not tell the user about function calls\n</IMPORTANT>' }}
|
| 54 |
+
{%- if messages[0].role == 'system' %}
|
| 55 |
+
{%- set content = render_content(messages[0].content, false, true)|trim %}
|
| 56 |
+
{%- if content %}
|
| 57 |
+
{{- '\n\n' + content }}
|
| 58 |
+
{%- endif %}
|
| 59 |
+
{%- endif %}
|
| 60 |
+
{{- '<|im_end|>\n' }}
|
| 61 |
+
{%- else %}
|
| 62 |
+
{%- if messages[0].role == 'system' %}
|
| 63 |
+
{%- set content = render_content(messages[0].content, false, true)|trim %}
|
| 64 |
+
{{- '<|im_start|>system\n' + content + '<|im_end|>\n' }}
|
| 65 |
+
{%- endif %}
|
| 66 |
+
{%- endif %}
|
| 67 |
+
{%- set ns = namespace(multi_step_tool=true, last_query_index=messages|length - 1) %}
|
| 68 |
+
{%- for message in messages[::-1] %}
|
| 69 |
+
{%- set index = (messages|length - 1) - loop.index0 %}
|
| 70 |
+
{%- if ns.multi_step_tool and message.role == "user" %}
|
| 71 |
+
{%- set content = render_content(message.content, false)|trim %}
|
| 72 |
+
{%- if not(content.startswith('<tool_response>') and content.endswith('</tool_response>')) %}
|
| 73 |
+
{%- set ns.multi_step_tool = false %}
|
| 74 |
+
{%- set ns.last_query_index = index %}
|
| 75 |
+
{%- endif %}
|
| 76 |
+
{%- endif %}
|
| 77 |
+
{%- endfor %}
|
| 78 |
+
{%- if ns.multi_step_tool %}
|
| 79 |
+
{{- raise_exception('No user query found in messages.') }}
|
| 80 |
+
{%- endif %}
|
| 81 |
+
{%- for message in messages %}
|
| 82 |
+
{%- set content = render_content(message.content, true)|trim %}
|
| 83 |
+
{%- if message.role == "system" %}
|
| 84 |
+
{%- if not loop.first %}
|
| 85 |
+
{{- raise_exception('System message must be at the beginning.') }}
|
| 86 |
+
{%- endif %}
|
| 87 |
+
{%- elif message.role == "user" %}
|
| 88 |
+
{{- '<|im_start|>' + message.role + '\n' + content + '<|im_end|>' + '\n' }}
|
| 89 |
+
{%- elif message.role == "assistant" %}
|
| 90 |
+
{%- set reasoning_content = '' %}
|
| 91 |
+
{%- if message.reasoning_content is string %}
|
| 92 |
+
{%- set reasoning_content = message.reasoning_content %}
|
| 93 |
+
{%- else %}
|
| 94 |
+
{%- if '</think>' in content %}
|
| 95 |
+
{%- set reasoning_content = content.split('</think>')[0].rstrip('\n').split('<think>')[-1].lstrip('\n') %}
|
| 96 |
+
{%- set content = content.split('</think>')[-1].lstrip('\n') %}
|
| 97 |
+
{%- endif %}
|
| 98 |
+
{%- endif %}
|
| 99 |
+
{%- set reasoning_content = reasoning_content|trim %}
|
| 100 |
+
{%- if loop.index0 > ns.last_query_index %}
|
| 101 |
+
{{- '<|im_start|>' + message.role + '\n<think>\n' + reasoning_content + '\n</think>\n\n' + content }}
|
| 102 |
+
{%- else %}
|
| 103 |
+
{{- '<|im_start|>' + message.role + '\n' + content }}
|
| 104 |
+
{%- endif %}
|
| 105 |
+
{%- if message.tool_calls and message.tool_calls is iterable and message.tool_calls is not mapping %}
|
| 106 |
+
{%- for tool_call in message.tool_calls %}
|
| 107 |
+
{%- if tool_call.function is defined %}
|
| 108 |
+
{%- set tool_call = tool_call.function %}
|
| 109 |
+
{%- endif %}
|
| 110 |
+
{%- if loop.first %}
|
| 111 |
+
{%- if content|trim %}
|
| 112 |
+
{{- '\n\n<tool_call>\n<function=' + tool_call.name + '>\n' }}
|
| 113 |
+
{%- else %}
|
| 114 |
+
{{- '<tool_call>\n<function=' + tool_call.name + '>\n' }}
|
| 115 |
+
{%- endif %}
|
| 116 |
+
{%- else %}
|
| 117 |
+
{{- '\n<tool_call>\n<function=' + tool_call.name + '>\n' }}
|
| 118 |
+
{%- endif %}
|
| 119 |
+
{%- if tool_call.arguments is defined %}
|
| 120 |
+
{%- for args_name, args_value in tool_call.arguments|items %}
|
| 121 |
+
{{- '<parameter=' + args_name + '>\n' }}
|
| 122 |
+
{%- set args_value = args_value | tojson | safe if args_value is mapping or (args_value is sequence and args_value is not string) else args_value | string %}
|
| 123 |
+
{{- args_value }}
|
| 124 |
+
{{- '\n</parameter>\n' }}
|
| 125 |
+
{%- endfor %}
|
| 126 |
+
{%- endif %}
|
| 127 |
+
{{- '</function>\n</tool_call>' }}
|
| 128 |
+
{%- endfor %}
|
| 129 |
+
{%- endif %}
|
| 130 |
+
{{- '<|im_end|>\n' }}
|
| 131 |
+
{%- elif message.role == "tool" %}
|
| 132 |
+
{%- if loop.previtem and loop.previtem.role != "tool" %}
|
| 133 |
+
{{- '<|im_start|>user' }}
|
| 134 |
+
{%- endif %}
|
| 135 |
+
{{- '\n<tool_response>\n' }}
|
| 136 |
+
{{- content }}
|
| 137 |
+
{{- '\n</tool_response>' }}
|
| 138 |
+
{%- if not loop.last and loop.nextitem.role != "tool" %}
|
| 139 |
+
{{- '<|im_end|>\n' }}
|
| 140 |
+
{%- elif loop.last %}
|
| 141 |
+
{{- '<|im_end|>\n' }}
|
| 142 |
+
{%- endif %}
|
| 143 |
+
{%- else %}
|
| 144 |
+
{{- raise_exception('Unexpected message role.') }}
|
| 145 |
+
{%- endif %}
|
| 146 |
+
{%- endfor %}
|
| 147 |
+
{%- if add_generation_prompt %}
|
| 148 |
+
{{- '<|im_start|>assistant\n' }}
|
| 149 |
+
{%- if enable_thinking is defined and enable_thinking is false %}
|
| 150 |
+
{{- '<think>\n\n</think>\n\n' }}
|
| 151 |
+
{%- else %}
|
| 152 |
+
{{- '<think>\n' }}
|
| 153 |
+
{%- endif %}
|
| 154 |
+
{%- endif %}
|
overgeneralisation_original_Swedish/Qwen3.5-4B-Base_overgeneralisation_splits_original_features_train_overgeneralisation_splits_original_features_test1/checkpoint-1060/tokenizer_config.json
ADDED
|
@@ -0,0 +1,31 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
{
|
| 2 |
+
"add_prefix_space": false,
|
| 3 |
+
"audio_bos_token": "<|audio_start|>",
|
| 4 |
+
"audio_eos_token": "<|audio_end|>",
|
| 5 |
+
"audio_token": "<|audio_pad|>",
|
| 6 |
+
"backend": "tokenizers",
|
| 7 |
+
"bos_token": null,
|
| 8 |
+
"clean_up_tokenization_spaces": false,
|
| 9 |
+
"eos_token": "<|endoftext|>",
|
| 10 |
+
"errors": "replace",
|
| 11 |
+
"image_token": "<|image_pad|>",
|
| 12 |
+
"is_local": false,
|
| 13 |
+
"model_max_length": 262144,
|
| 14 |
+
"model_specific_special_tokens": {
|
| 15 |
+
"audio_bos_token": "<|audio_start|>",
|
| 16 |
+
"audio_eos_token": "<|audio_end|>",
|
| 17 |
+
"audio_token": "<|audio_pad|>",
|
| 18 |
+
"image_token": "<|image_pad|>",
|
| 19 |
+
"video_token": "<|video_pad|>",
|
| 20 |
+
"vision_bos_token": "<|vision_start|>",
|
| 21 |
+
"vision_eos_token": "<|vision_end|>"
|
| 22 |
+
},
|
| 23 |
+
"pad_token": "<|endoftext|>",
|
| 24 |
+
"pretokenize_regex": "(?i:'s|'t|'re|'ve|'m|'ll|'d)|[^\\r\\n\\p{L}\\p{N}]?[\\p{L}\\p{M}]+|\\p{N}| ?[^\\s\\p{L}\\p{M}\\p{N}]+[\\r\\n]*|\\s*[\\r\\n]+|\\s+(?!\\S)|\\s+",
|
| 25 |
+
"split_special_tokens": false,
|
| 26 |
+
"tokenizer_class": "TokenizersBackend",
|
| 27 |
+
"unk_token": null,
|
| 28 |
+
"video_token": "<|video_pad|>",
|
| 29 |
+
"vision_bos_token": "<|vision_start|>",
|
| 30 |
+
"vision_eos_token": "<|vision_end|>"
|
| 31 |
+
}
|
overgeneralisation_original_Swedish/Qwen3.5-4B-Base_overgeneralisation_splits_original_features_train_overgeneralisation_splits_original_features_test1/checkpoint-1060/trainer_state.json
ADDED
|
@@ -0,0 +1,1147 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
{
|
| 2 |
+
"best_global_step": null,
|
| 3 |
+
"best_metric": null,
|
| 4 |
+
"best_model_checkpoint": null,
|
| 5 |
+
"epoch": 2.6376089663760895,
|
| 6 |
+
"eval_steps": 20,
|
| 7 |
+
"global_step": 1060,
|
| 8 |
+
"is_hyper_param_search": false,
|
| 9 |
+
"is_local_process_zero": true,
|
| 10 |
+
"is_world_process_zero": true,
|
| 11 |
+
"log_history": [
|
| 12 |
+
{
|
| 13 |
+
"entropy": 1.9784346982836722,
|
| 14 |
+
"epoch": 0.049813200498132,
|
| 15 |
+
"grad_norm": 3.0229668617248535,
|
| 16 |
+
"learning_rate": 9.526142962415369e-06,
|
| 17 |
+
"loss": 1.7360023498535155,
|
| 18 |
+
"mean_token_accuracy": 0.6449888605624438,
|
| 19 |
+
"num_tokens": 46794.0,
|
| 20 |
+
"step": 20
|
| 21 |
+
},
|
| 22 |
+
{
|
| 23 |
+
"epoch": 0.049813200498132,
|
| 24 |
+
"eval_entropy": 1.41506897571475,
|
| 25 |
+
"eval_loss": 1.1876318454742432,
|
| 26 |
+
"eval_mean_token_accuracy": 0.734131895525511,
|
| 27 |
+
"eval_num_tokens": 46794.0,
|
| 28 |
+
"eval_runtime": 87.8071,
|
| 29 |
+
"eval_samples_per_second": 15.671,
|
| 30 |
+
"eval_steps_per_second": 1.959,
|
| 31 |
+
"step": 20
|
| 32 |
+
},
|
| 33 |
+
{
|
| 34 |
+
"entropy": 1.049924298375845,
|
| 35 |
+
"epoch": 0.099626400996264,
|
| 36 |
+
"grad_norm": 1.5795097351074219,
|
| 37 |
+
"learning_rate": 1.9553661870221022e-05,
|
| 38 |
+
"loss": 0.8944448471069336,
|
| 39 |
+
"mean_token_accuracy": 0.7748479396104813,
|
| 40 |
+
"num_tokens": 90754.0,
|
| 41 |
+
"step": 40
|
| 42 |
+
},
|
| 43 |
+
{
|
| 44 |
+
"epoch": 0.099626400996264,
|
| 45 |
+
"eval_entropy": 0.7996658658565476,
|
| 46 |
+
"eval_loss": 0.7202735543251038,
|
| 47 |
+
"eval_mean_token_accuracy": 0.8070558306089667,
|
| 48 |
+
"eval_num_tokens": 90754.0,
|
| 49 |
+
"eval_runtime": 86.9199,
|
| 50 |
+
"eval_samples_per_second": 15.831,
|
| 51 |
+
"eval_steps_per_second": 1.979,
|
| 52 |
+
"step": 40
|
| 53 |
+
},
|
| 54 |
+
{
|
| 55 |
+
"entropy": 0.7734908878803253,
|
| 56 |
+
"epoch": 0.149439601494396,
|
| 57 |
+
"grad_norm": 1.3136248588562012,
|
| 58 |
+
"learning_rate": 2.9581180778026673e-05,
|
| 59 |
+
"loss": 0.6780608654022217,
|
| 60 |
+
"mean_token_accuracy": 0.8168170280754566,
|
| 61 |
+
"num_tokens": 137472.0,
|
| 62 |
+
"step": 60
|
| 63 |
+
},
|
| 64 |
+
{
|
| 65 |
+
"epoch": 0.149439601494396,
|
| 66 |
+
"eval_entropy": 0.7119324009778888,
|
| 67 |
+
"eval_loss": 0.6554311513900757,
|
| 68 |
+
"eval_mean_token_accuracy": 0.8215604798738346,
|
| 69 |
+
"eval_num_tokens": 137472.0,
|
| 70 |
+
"eval_runtime": 86.8692,
|
| 71 |
+
"eval_samples_per_second": 15.84,
|
| 72 |
+
"eval_steps_per_second": 1.98,
|
| 73 |
+
"step": 60
|
| 74 |
+
},
|
| 75 |
+
{
|
| 76 |
+
"entropy": 0.7071127541363239,
|
| 77 |
+
"epoch": 0.199252801992528,
|
| 78 |
+
"grad_norm": 1.387060284614563,
|
| 79 |
+
"learning_rate": 3.960869968583232e-05,
|
| 80 |
+
"loss": 0.6382100582122803,
|
| 81 |
+
"mean_token_accuracy": 0.8229366384446621,
|
| 82 |
+
"num_tokens": 187408.0,
|
| 83 |
+
"step": 80
|
| 84 |
+
},
|
| 85 |
+
{
|
| 86 |
+
"epoch": 0.199252801992528,
|
| 87 |
+
"eval_entropy": 0.6883931482254073,
|
| 88 |
+
"eval_loss": 0.625065803527832,
|
| 89 |
+
"eval_mean_token_accuracy": 0.828940509710201,
|
| 90 |
+
"eval_num_tokens": 187408.0,
|
| 91 |
+
"eval_runtime": 86.662,
|
| 92 |
+
"eval_samples_per_second": 15.878,
|
| 93 |
+
"eval_steps_per_second": 1.985,
|
| 94 |
+
"step": 80
|
| 95 |
+
},
|
| 96 |
+
{
|
| 97 |
+
"entropy": 0.6800824083387852,
|
| 98 |
+
"epoch": 0.24906600249066002,
|
| 99 |
+
"grad_norm": 0.9892916679382324,
|
| 100 |
+
"learning_rate": 4.963621859363797e-05,
|
| 101 |
+
"loss": 0.6011715888977051,
|
| 102 |
+
"mean_token_accuracy": 0.8323964163661003,
|
| 103 |
+
"num_tokens": 234197.0,
|
| 104 |
+
"step": 100
|
| 105 |
+
},
|
| 106 |
+
{
|
| 107 |
+
"epoch": 0.24906600249066002,
|
| 108 |
+
"eval_entropy": 0.6840810470802839,
|
| 109 |
+
"eval_loss": 0.6037028431892395,
|
| 110 |
+
"eval_mean_token_accuracy": 0.8309669033732525,
|
| 111 |
+
"eval_num_tokens": 234197.0,
|
| 112 |
+
"eval_runtime": 86.4637,
|
| 113 |
+
"eval_samples_per_second": 15.914,
|
| 114 |
+
"eval_steps_per_second": 1.989,
|
| 115 |
+
"step": 100
|
| 116 |
+
},
|
| 117 |
+
{
|
| 118 |
+
"entropy": 0.6776216626167297,
|
| 119 |
+
"epoch": 0.298879202988792,
|
| 120 |
+
"grad_norm": 0.8918434977531433,
|
| 121 |
+
"learning_rate": 5.9663737501443624e-05,
|
| 122 |
+
"loss": 0.5991742610931396,
|
| 123 |
+
"mean_token_accuracy": 0.8300838828086853,
|
| 124 |
+
"num_tokens": 281241.0,
|
| 125 |
+
"step": 120
|
| 126 |
+
},
|
| 127 |
+
{
|
| 128 |
+
"epoch": 0.298879202988792,
|
| 129 |
+
"eval_entropy": 0.690427724705186,
|
| 130 |
+
"eval_loss": 0.5939701795578003,
|
| 131 |
+
"eval_mean_token_accuracy": 0.8345950186945671,
|
| 132 |
+
"eval_num_tokens": 281241.0,
|
| 133 |
+
"eval_runtime": 86.6626,
|
| 134 |
+
"eval_samples_per_second": 15.878,
|
| 135 |
+
"eval_steps_per_second": 1.985,
|
| 136 |
+
"step": 120
|
| 137 |
+
},
|
| 138 |
+
{
|
| 139 |
+
"entropy": 0.6709842771291733,
|
| 140 |
+
"epoch": 0.34869240348692404,
|
| 141 |
+
"grad_norm": 0.9135531187057495,
|
| 142 |
+
"learning_rate": 6.969125640924927e-05,
|
| 143 |
+
"loss": 0.5914147377014161,
|
| 144 |
+
"mean_token_accuracy": 0.8314545609056949,
|
| 145 |
+
"num_tokens": 327393.0,
|
| 146 |
+
"step": 140
|
| 147 |
+
},
|
| 148 |
+
{
|
| 149 |
+
"epoch": 0.34869240348692404,
|
| 150 |
+
"eval_entropy": 0.6584504666023476,
|
| 151 |
+
"eval_loss": 0.5849721431732178,
|
| 152 |
+
"eval_mean_token_accuracy": 0.8357757236375365,
|
| 153 |
+
"eval_num_tokens": 327393.0,
|
| 154 |
+
"eval_runtime": 86.3262,
|
| 155 |
+
"eval_samples_per_second": 15.94,
|
| 156 |
+
"eval_steps_per_second": 1.992,
|
| 157 |
+
"step": 140
|
| 158 |
+
},
|
| 159 |
+
{
|
| 160 |
+
"entropy": 0.6524647936224938,
|
| 161 |
+
"epoch": 0.398505603985056,
|
| 162 |
+
"grad_norm": 0.8651587963104248,
|
| 163 |
+
"learning_rate": 7.971877531705493e-05,
|
| 164 |
+
"loss": 0.5710843563079834,
|
| 165 |
+
"mean_token_accuracy": 0.8396127380430698,
|
| 166 |
+
"num_tokens": 373834.0,
|
| 167 |
+
"step": 160
|
| 168 |
+
},
|
| 169 |
+
{
|
| 170 |
+
"epoch": 0.398505603985056,
|
| 171 |
+
"eval_entropy": 0.6283470298661742,
|
| 172 |
+
"eval_loss": 0.5738973617553711,
|
| 173 |
+
"eval_mean_token_accuracy": 0.8379981181649274,
|
| 174 |
+
"eval_num_tokens": 373834.0,
|
| 175 |
+
"eval_runtime": 86.5619,
|
| 176 |
+
"eval_samples_per_second": 15.896,
|
| 177 |
+
"eval_steps_per_second": 1.987,
|
| 178 |
+
"step": 160
|
| 179 |
+
},
|
| 180 |
+
{
|
| 181 |
+
"entropy": 0.6450445972383022,
|
| 182 |
+
"epoch": 0.44831880448318806,
|
| 183 |
+
"grad_norm": 0.8661723732948303,
|
| 184 |
+
"learning_rate": 8.974629422486058e-05,
|
| 185 |
+
"loss": 0.5677794933319091,
|
| 186 |
+
"mean_token_accuracy": 0.8389350369572639,
|
| 187 |
+
"num_tokens": 422572.0,
|
| 188 |
+
"step": 180
|
| 189 |
+
},
|
| 190 |
+
{
|
| 191 |
+
"epoch": 0.44831880448318806,
|
| 192 |
+
"eval_entropy": 0.6142613257086554,
|
| 193 |
+
"eval_loss": 0.5698265433311462,
|
| 194 |
+
"eval_mean_token_accuracy": 0.8388577273418737,
|
| 195 |
+
"eval_num_tokens": 422572.0,
|
| 196 |
+
"eval_runtime": 86.4443,
|
| 197 |
+
"eval_samples_per_second": 15.918,
|
| 198 |
+
"eval_steps_per_second": 1.99,
|
| 199 |
+
"step": 180
|
| 200 |
+
},
|
| 201 |
+
{
|
| 202 |
+
"entropy": 0.6448334597051144,
|
| 203 |
+
"epoch": 0.49813200498132004,
|
| 204 |
+
"grad_norm": 0.9662242531776428,
|
| 205 |
+
"learning_rate": 9.977381313266624e-05,
|
| 206 |
+
"loss": 0.581433916091919,
|
| 207 |
+
"mean_token_accuracy": 0.8387043006718159,
|
| 208 |
+
"num_tokens": 471879.0,
|
| 209 |
+
"step": 200
|
| 210 |
+
},
|
| 211 |
+
{
|
| 212 |
+
"epoch": 0.49813200498132004,
|
| 213 |
+
"eval_entropy": 0.6154296522916749,
|
| 214 |
+
"eval_loss": 0.5660303831100464,
|
| 215 |
+
"eval_mean_token_accuracy": 0.8412494766850804,
|
| 216 |
+
"eval_num_tokens": 471879.0,
|
| 217 |
+
"eval_runtime": 86.3063,
|
| 218 |
+
"eval_samples_per_second": 15.943,
|
| 219 |
+
"eval_steps_per_second": 1.993,
|
| 220 |
+
"step": 200
|
| 221 |
+
},
|
| 222 |
+
{
|
| 223 |
+
"entropy": 0.6376728117465973,
|
| 224 |
+
"epoch": 0.547945205479452,
|
| 225 |
+
"grad_norm": 0.7618638873100281,
|
| 226 |
+
"learning_rate": 0.00010980133204047189,
|
| 227 |
+
"loss": 0.5678351402282715,
|
| 228 |
+
"mean_token_accuracy": 0.8404546812176704,
|
| 229 |
+
"num_tokens": 520984.0,
|
| 230 |
+
"step": 220
|
| 231 |
+
},
|
| 232 |
+
{
|
| 233 |
+
"epoch": 0.547945205479452,
|
| 234 |
+
"eval_entropy": 0.6181817033956217,
|
| 235 |
+
"eval_loss": 0.5663750171661377,
|
| 236 |
+
"eval_mean_token_accuracy": 0.8388350962899452,
|
| 237 |
+
"eval_num_tokens": 520984.0,
|
| 238 |
+
"eval_runtime": 86.5904,
|
| 239 |
+
"eval_samples_per_second": 15.891,
|
| 240 |
+
"eval_steps_per_second": 1.986,
|
| 241 |
+
"step": 220
|
| 242 |
+
},
|
| 243 |
+
{
|
| 244 |
+
"entropy": 0.6303176879882812,
|
| 245 |
+
"epoch": 0.597758405977584,
|
| 246 |
+
"grad_norm": 0.7571695446968079,
|
| 247 |
+
"learning_rate": 0.00011982885094827753,
|
| 248 |
+
"loss": 0.5502778053283691,
|
| 249 |
+
"mean_token_accuracy": 0.8429657347500324,
|
| 250 |
+
"num_tokens": 566596.0,
|
| 251 |
+
"step": 240
|
| 252 |
+
},
|
| 253 |
+
{
|
| 254 |
+
"epoch": 0.597758405977584,
|
| 255 |
+
"eval_entropy": 0.6252533817707107,
|
| 256 |
+
"eval_loss": 0.5570284128189087,
|
| 257 |
+
"eval_mean_token_accuracy": 0.8427327847064927,
|
| 258 |
+
"eval_num_tokens": 566596.0,
|
| 259 |
+
"eval_runtime": 86.4157,
|
| 260 |
+
"eval_samples_per_second": 15.923,
|
| 261 |
+
"eval_steps_per_second": 1.99,
|
| 262 |
+
"step": 240
|
| 263 |
+
},
|
| 264 |
+
{
|
| 265 |
+
"entropy": 0.6202544964849949,
|
| 266 |
+
"epoch": 0.6475716064757161,
|
| 267 |
+
"grad_norm": 0.6447190642356873,
|
| 268 |
+
"learning_rate": 0.00012985636985608318,
|
| 269 |
+
"loss": 0.5485352993011474,
|
| 270 |
+
"mean_token_accuracy": 0.844165726006031,
|
| 271 |
+
"num_tokens": 613603.0,
|
| 272 |
+
"step": 260
|
| 273 |
+
},
|
| 274 |
+
{
|
| 275 |
+
"epoch": 0.6475716064757161,
|
| 276 |
+
"eval_entropy": 0.6441633552312851,
|
| 277 |
+
"eval_loss": 0.5606644153594971,
|
| 278 |
+
"eval_mean_token_accuracy": 0.842403513054515,
|
| 279 |
+
"eval_num_tokens": 613603.0,
|
| 280 |
+
"eval_runtime": 86.6343,
|
| 281 |
+
"eval_samples_per_second": 15.883,
|
| 282 |
+
"eval_steps_per_second": 1.985,
|
| 283 |
+
"step": 260
|
| 284 |
+
},
|
| 285 |
+
{
|
| 286 |
+
"entropy": 0.6306711677461863,
|
| 287 |
+
"epoch": 0.6973848069738481,
|
| 288 |
+
"grad_norm": 0.7869907021522522,
|
| 289 |
+
"learning_rate": 0.00013988388876388883,
|
| 290 |
+
"loss": 0.5579307556152344,
|
| 291 |
+
"mean_token_accuracy": 0.841247134655714,
|
| 292 |
+
"num_tokens": 658565.0,
|
| 293 |
+
"step": 280
|
| 294 |
+
},
|
| 295 |
+
{
|
| 296 |
+
"epoch": 0.6973848069738481,
|
| 297 |
+
"eval_entropy": 0.6263934678809587,
|
| 298 |
+
"eval_loss": 0.5559113025665283,
|
| 299 |
+
"eval_mean_token_accuracy": 0.8427334743183713,
|
| 300 |
+
"eval_num_tokens": 658565.0,
|
| 301 |
+
"eval_runtime": 86.6403,
|
| 302 |
+
"eval_samples_per_second": 15.882,
|
| 303 |
+
"eval_steps_per_second": 1.985,
|
| 304 |
+
"step": 280
|
| 305 |
+
},
|
| 306 |
+
{
|
| 307 |
+
"entropy": 0.6385872110724449,
|
| 308 |
+
"epoch": 0.7471980074719801,
|
| 309 |
+
"grad_norm": 0.6679229736328125,
|
| 310 |
+
"learning_rate": 0.0001499114076716945,
|
| 311 |
+
"loss": 0.5667279720306396,
|
| 312 |
+
"mean_token_accuracy": 0.8389136254787445,
|
| 313 |
+
"num_tokens": 705680.0,
|
| 314 |
+
"step": 300
|
| 315 |
+
},
|
| 316 |
+
{
|
| 317 |
+
"epoch": 0.7471980074719801,
|
| 318 |
+
"eval_entropy": 0.6141417321077612,
|
| 319 |
+
"eval_loss": 0.5570600628852844,
|
| 320 |
+
"eval_mean_token_accuracy": 0.8437647996253745,
|
| 321 |
+
"eval_num_tokens": 705680.0,
|
| 322 |
+
"eval_runtime": 86.7588,
|
| 323 |
+
"eval_samples_per_second": 15.86,
|
| 324 |
+
"eval_steps_per_second": 1.983,
|
| 325 |
+
"step": 300
|
| 326 |
+
},
|
| 327 |
+
{
|
| 328 |
+
"entropy": 0.6199494235217571,
|
| 329 |
+
"epoch": 0.797011207970112,
|
| 330 |
+
"grad_norm": 0.7924400568008423,
|
| 331 |
+
"learning_rate": 0.00015993892657950015,
|
| 332 |
+
"loss": 0.5529299736022949,
|
| 333 |
+
"mean_token_accuracy": 0.8426973208785057,
|
| 334 |
+
"num_tokens": 752616.0,
|
| 335 |
+
"step": 320
|
| 336 |
+
},
|
| 337 |
+
{
|
| 338 |
+
"epoch": 0.797011207970112,
|
| 339 |
+
"eval_entropy": 0.6133768925833147,
|
| 340 |
+
"eval_loss": 0.556602418422699,
|
| 341 |
+
"eval_mean_token_accuracy": 0.8432947965555413,
|
| 342 |
+
"eval_num_tokens": 752616.0,
|
| 343 |
+
"eval_runtime": 86.492,
|
| 344 |
+
"eval_samples_per_second": 15.909,
|
| 345 |
+
"eval_steps_per_second": 1.989,
|
| 346 |
+
"step": 320
|
| 347 |
+
},
|
| 348 |
+
{
|
| 349 |
+
"entropy": 0.6203986253589392,
|
| 350 |
+
"epoch": 0.8468244084682441,
|
| 351 |
+
"grad_norm": 0.8364354372024536,
|
| 352 |
+
"learning_rate": 0.00016996644548730578,
|
| 353 |
+
"loss": 0.5551144123077393,
|
| 354 |
+
"mean_token_accuracy": 0.8432973213493824,
|
| 355 |
+
"num_tokens": 797151.0,
|
| 356 |
+
"step": 340
|
| 357 |
+
},
|
| 358 |
+
{
|
| 359 |
+
"epoch": 0.8468244084682441,
|
| 360 |
+
"eval_entropy": 0.6017442844634833,
|
| 361 |
+
"eval_loss": 0.5566568374633789,
|
| 362 |
+
"eval_mean_token_accuracy": 0.8437666123689607,
|
| 363 |
+
"eval_num_tokens": 797151.0,
|
| 364 |
+
"eval_runtime": 86.5552,
|
| 365 |
+
"eval_samples_per_second": 15.897,
|
| 366 |
+
"eval_steps_per_second": 1.987,
|
| 367 |
+
"step": 340
|
| 368 |
+
},
|
| 369 |
+
{
|
| 370 |
+
"entropy": 0.6341533534228802,
|
| 371 |
+
"epoch": 0.8966376089663761,
|
| 372 |
+
"grad_norm": 0.7783445715904236,
|
| 373 |
+
"learning_rate": 0.00017999396439511144,
|
| 374 |
+
"loss": 0.5669133186340332,
|
| 375 |
+
"mean_token_accuracy": 0.8379446342587471,
|
| 376 |
+
"num_tokens": 843585.0,
|
| 377 |
+
"step": 360
|
| 378 |
+
},
|
| 379 |
+
{
|
| 380 |
+
"epoch": 0.8966376089663761,
|
| 381 |
+
"eval_entropy": 0.6055107958788095,
|
| 382 |
+
"eval_loss": 0.5599350333213806,
|
| 383 |
+
"eval_mean_token_accuracy": 0.8435030894917112,
|
| 384 |
+
"eval_num_tokens": 843585.0,
|
| 385 |
+
"eval_runtime": 86.4814,
|
| 386 |
+
"eval_samples_per_second": 15.911,
|
| 387 |
+
"eval_steps_per_second": 1.989,
|
| 388 |
+
"step": 360
|
| 389 |
+
},
|
| 390 |
+
{
|
| 391 |
+
"entropy": 0.6306198488920927,
|
| 392 |
+
"epoch": 0.9464508094645081,
|
| 393 |
+
"grad_norm": 0.8449786901473999,
|
| 394 |
+
"learning_rate": 0.0001900214833029171,
|
| 395 |
+
"loss": 0.5739435195922852,
|
| 396 |
+
"mean_token_accuracy": 0.8393832489848136,
|
| 397 |
+
"num_tokens": 889842.0,
|
| 398 |
+
"step": 380
|
| 399 |
+
},
|
| 400 |
+
{
|
| 401 |
+
"epoch": 0.9464508094645081,
|
| 402 |
+
"eval_entropy": 0.6129532439071078,
|
| 403 |
+
"eval_loss": 0.5566295981407166,
|
| 404 |
+
"eval_mean_token_accuracy": 0.8430350880290187,
|
| 405 |
+
"eval_num_tokens": 889842.0,
|
| 406 |
+
"eval_runtime": 86.4643,
|
| 407 |
+
"eval_samples_per_second": 15.914,
|
| 408 |
+
"eval_steps_per_second": 1.989,
|
| 409 |
+
"step": 380
|
| 410 |
+
},
|
| 411 |
+
{
|
| 412 |
+
"entropy": 0.6203123550862074,
|
| 413 |
+
"epoch": 0.9962640099626401,
|
| 414 |
+
"grad_norm": 0.7334314584732056,
|
| 415 |
+
"learning_rate": 0.00020004900221072276,
|
| 416 |
+
"loss": 0.5547565937042236,
|
| 417 |
+
"mean_token_accuracy": 0.8403573960065842,
|
| 418 |
+
"num_tokens": 935589.0,
|
| 419 |
+
"step": 400
|
| 420 |
+
},
|
| 421 |
+
{
|
| 422 |
+
"epoch": 0.9962640099626401,
|
| 423 |
+
"eval_entropy": 0.6275761647279873,
|
| 424 |
+
"eval_loss": 0.5621116757392883,
|
| 425 |
+
"eval_mean_token_accuracy": 0.841587379228237,
|
| 426 |
+
"eval_num_tokens": 935589.0,
|
| 427 |
+
"eval_runtime": 86.4748,
|
| 428 |
+
"eval_samples_per_second": 15.912,
|
| 429 |
+
"eval_steps_per_second": 1.989,
|
| 430 |
+
"step": 400
|
| 431 |
+
},
|
| 432 |
+
{
|
| 433 |
+
"entropy": 0.5795013002860241,
|
| 434 |
+
"epoch": 1.0448318804483188,
|
| 435 |
+
"grad_norm": 0.8858296871185303,
|
| 436 |
+
"learning_rate": 0.0002015421505577756,
|
| 437 |
+
"loss": 0.5183939933776855,
|
| 438 |
+
"mean_token_accuracy": 0.850081592034071,
|
| 439 |
+
"num_tokens": 980589.0,
|
| 440 |
+
"step": 420
|
| 441 |
+
},
|
| 442 |
+
{
|
| 443 |
+
"epoch": 1.0448318804483188,
|
| 444 |
+
"eval_entropy": 0.5583065545489622,
|
| 445 |
+
"eval_loss": 0.5605642199516296,
|
| 446 |
+
"eval_mean_token_accuracy": 0.8439708411000496,
|
| 447 |
+
"eval_num_tokens": 980589.0,
|
| 448 |
+
"eval_runtime": 86.5422,
|
| 449 |
+
"eval_samples_per_second": 15.9,
|
| 450 |
+
"eval_steps_per_second": 1.987,
|
| 451 |
+
"step": 420
|
| 452 |
+
},
|
| 453 |
+
{
|
| 454 |
+
"entropy": 0.5671238023787737,
|
| 455 |
+
"epoch": 1.0946450809464507,
|
| 456 |
+
"grad_norm": 0.6882498264312744,
|
| 457 |
+
"learning_rate": 0.00020150112347025443,
|
| 458 |
+
"loss": 0.5077326774597168,
|
| 459 |
+
"mean_token_accuracy": 0.8489868573844432,
|
| 460 |
+
"num_tokens": 1027852.0,
|
| 461 |
+
"step": 440
|
| 462 |
+
},
|
| 463 |
+
{
|
| 464 |
+
"epoch": 1.0946450809464507,
|
| 465 |
+
"eval_entropy": 0.5868900277933409,
|
| 466 |
+
"eval_loss": 0.5602695345878601,
|
| 467 |
+
"eval_mean_token_accuracy": 0.8428842161977014,
|
| 468 |
+
"eval_num_tokens": 1027852.0,
|
| 469 |
+
"eval_runtime": 86.623,
|
| 470 |
+
"eval_samples_per_second": 15.885,
|
| 471 |
+
"eval_steps_per_second": 1.986,
|
| 472 |
+
"step": 440
|
| 473 |
+
},
|
| 474 |
+
{
|
| 475 |
+
"entropy": 0.5533561781048775,
|
| 476 |
+
"epoch": 1.1444582814445827,
|
| 477 |
+
"grad_norm": 0.7717723250389099,
|
| 478 |
+
"learning_rate": 0.0002014297192297181,
|
| 479 |
+
"loss": 0.4954517364501953,
|
| 480 |
+
"mean_token_accuracy": 0.8529035650193691,
|
| 481 |
+
"num_tokens": 1077649.0,
|
| 482 |
+
"step": 460
|
| 483 |
+
},
|
| 484 |
+
{
|
| 485 |
+
"epoch": 1.1444582814445827,
|
| 486 |
+
"eval_entropy": 0.5600803743961246,
|
| 487 |
+
"eval_loss": 0.5608077645301819,
|
| 488 |
+
"eval_mean_token_accuracy": 0.8445036771685578,
|
| 489 |
+
"eval_num_tokens": 1077649.0,
|
| 490 |
+
"eval_runtime": 86.1316,
|
| 491 |
+
"eval_samples_per_second": 15.976,
|
| 492 |
+
"eval_steps_per_second": 1.997,
|
| 493 |
+
"step": 460
|
| 494 |
+
},
|
| 495 |
+
{
|
| 496 |
+
"entropy": 0.5692154694348573,
|
| 497 |
+
"epoch": 1.1942714819427147,
|
| 498 |
+
"grad_norm": 0.7322827577590942,
|
| 499 |
+
"learning_rate": 0.0002013279593707117,
|
| 500 |
+
"loss": 0.505049467086792,
|
| 501 |
+
"mean_token_accuracy": 0.8551576808094978,
|
| 502 |
+
"num_tokens": 1124872.0,
|
| 503 |
+
"step": 480
|
| 504 |
+
},
|
| 505 |
+
{
|
| 506 |
+
"epoch": 1.1942714819427147,
|
| 507 |
+
"eval_entropy": 0.5732695829383162,
|
| 508 |
+
"eval_loss": 0.5594323873519897,
|
| 509 |
+
"eval_mean_token_accuracy": 0.8449713407560836,
|
| 510 |
+
"eval_num_tokens": 1124872.0,
|
| 511 |
+
"eval_runtime": 86.2726,
|
| 512 |
+
"eval_samples_per_second": 15.949,
|
| 513 |
+
"eval_steps_per_second": 1.994,
|
| 514 |
+
"step": 480
|
| 515 |
+
},
|
| 516 |
+
{
|
| 517 |
+
"entropy": 0.5817618492990733,
|
| 518 |
+
"epoch": 1.244084682440847,
|
| 519 |
+
"grad_norm": 1.1776764392852783,
|
| 520 |
+
"learning_rate": 0.0002011958745826208,
|
| 521 |
+
"loss": 0.5137609958648681,
|
| 522 |
+
"mean_token_accuracy": 0.8521522544324398,
|
| 523 |
+
"num_tokens": 1168698.0,
|
| 524 |
+
"step": 500
|
| 525 |
+
},
|
| 526 |
+
{
|
| 527 |
+
"epoch": 1.244084682440847,
|
| 528 |
+
"eval_entropy": 0.5662581343636957,
|
| 529 |
+
"eval_loss": 0.5595026016235352,
|
| 530 |
+
"eval_mean_token_accuracy": 0.8441977164773053,
|
| 531 |
+
"eval_num_tokens": 1168698.0,
|
| 532 |
+
"eval_runtime": 86.7261,
|
| 533 |
+
"eval_samples_per_second": 15.866,
|
| 534 |
+
"eval_steps_per_second": 1.983,
|
| 535 |
+
"step": 500
|
| 536 |
+
},
|
| 537 |
+
{
|
| 538 |
+
"entropy": 0.5712925456464291,
|
| 539 |
+
"epoch": 1.293897882938979,
|
| 540 |
+
"grad_norm": 0.7960361838340759,
|
| 541 |
+
"learning_rate": 0.0002010335047004159,
|
| 542 |
+
"loss": 0.5134767532348633,
|
| 543 |
+
"mean_token_accuracy": 0.8513577707111836,
|
| 544 |
+
"num_tokens": 1216679.0,
|
| 545 |
+
"step": 520
|
| 546 |
+
},
|
| 547 |
+
{
|
| 548 |
+
"epoch": 1.293897882938979,
|
| 549 |
+
"eval_entropy": 0.5441222797299541,
|
| 550 |
+
"eval_loss": 0.5535460114479065,
|
| 551 |
+
"eval_mean_token_accuracy": 0.8450886118550633,
|
| 552 |
+
"eval_num_tokens": 1216679.0,
|
| 553 |
+
"eval_runtime": 86.2675,
|
| 554 |
+
"eval_samples_per_second": 15.95,
|
| 555 |
+
"eval_steps_per_second": 1.994,
|
| 556 |
+
"step": 520
|
| 557 |
+
},
|
| 558 |
+
{
|
| 559 |
+
"entropy": 0.5787045754492283,
|
| 560 |
+
"epoch": 1.3437110834371109,
|
| 561 |
+
"grad_norm": 0.9205410480499268,
|
| 562 |
+
"learning_rate": 0.00020084089869263887,
|
| 563 |
+
"loss": 0.5119701862335205,
|
| 564 |
+
"mean_token_accuracy": 0.8503516331315041,
|
| 565 |
+
"num_tokens": 1261365.0,
|
| 566 |
+
"step": 540
|
| 567 |
+
},
|
| 568 |
+
{
|
| 569 |
+
"epoch": 1.3437110834371109,
|
| 570 |
+
"eval_entropy": 0.5744457827057949,
|
| 571 |
+
"eval_loss": 0.5514978766441345,
|
| 572 |
+
"eval_mean_token_accuracy": 0.845929987901865,
|
| 573 |
+
"eval_num_tokens": 1261365.0,
|
| 574 |
+
"eval_runtime": 86.2299,
|
| 575 |
+
"eval_samples_per_second": 15.957,
|
| 576 |
+
"eval_steps_per_second": 1.995,
|
| 577 |
+
"step": 540
|
| 578 |
+
},
|
| 579 |
+
{
|
| 580 |
+
"entropy": 0.5739392962306737,
|
| 581 |
+
"epoch": 1.3935242839352429,
|
| 582 |
+
"grad_norm": 0.7475653886795044,
|
| 583 |
+
"learning_rate": 0.00020061811464663464,
|
| 584 |
+
"loss": 0.5189042091369629,
|
| 585 |
+
"mean_token_accuracy": 0.8492388024926185,
|
| 586 |
+
"num_tokens": 1306879.0,
|
| 587 |
+
"step": 560
|
| 588 |
+
},
|
| 589 |
+
{
|
| 590 |
+
"epoch": 1.3935242839352429,
|
| 591 |
+
"eval_entropy": 0.6116398271433142,
|
| 592 |
+
"eval_loss": 0.551732063293457,
|
| 593 |
+
"eval_mean_token_accuracy": 0.8450756967067719,
|
| 594 |
+
"eval_num_tokens": 1306879.0,
|
| 595 |
+
"eval_runtime": 86.6081,
|
| 596 |
+
"eval_samples_per_second": 15.888,
|
| 597 |
+
"eval_steps_per_second": 1.986,
|
| 598 |
+
"step": 560
|
| 599 |
+
},
|
| 600 |
+
{
|
| 601 |
+
"entropy": 0.5755622573196888,
|
| 602 |
+
"epoch": 1.4433374844333748,
|
| 603 |
+
"grad_norm": 0.8218411803245544,
|
| 604 |
+
"learning_rate": 0.00020036521975103286,
|
| 605 |
+
"loss": 0.5106248378753662,
|
| 606 |
+
"mean_token_accuracy": 0.8506785586476326,
|
| 607 |
+
"num_tokens": 1353534.0,
|
| 608 |
+
"step": 580
|
| 609 |
+
},
|
| 610 |
+
{
|
| 611 |
+
"epoch": 1.4433374844333748,
|
| 612 |
+
"eval_entropy": 0.5906928708386976,
|
| 613 |
+
"eval_loss": 0.551278829574585,
|
| 614 |
+
"eval_mean_token_accuracy": 0.8462819308042526,
|
| 615 |
+
"eval_num_tokens": 1353534.0,
|
| 616 |
+
"eval_runtime": 86.5438,
|
| 617 |
+
"eval_samples_per_second": 15.899,
|
| 618 |
+
"eval_steps_per_second": 1.987,
|
| 619 |
+
"step": 580
|
| 620 |
+
},
|
| 621 |
+
{
|
| 622 |
+
"entropy": 0.5694822132587433,
|
| 623 |
+
"epoch": 1.4931506849315068,
|
| 624 |
+
"grad_norm": 0.8880652189254761,
|
| 625 |
+
"learning_rate": 0.00020008229027548475,
|
| 626 |
+
"loss": 0.5140334606170655,
|
| 627 |
+
"mean_token_accuracy": 0.8521522797644139,
|
| 628 |
+
"num_tokens": 1399537.0,
|
| 629 |
+
"step": 600
|
| 630 |
+
},
|
| 631 |
+
{
|
| 632 |
+
"epoch": 1.4931506849315068,
|
| 633 |
+
"eval_entropy": 0.5599641964532608,
|
| 634 |
+
"eval_loss": 0.5501875877380371,
|
| 635 |
+
"eval_mean_token_accuracy": 0.8467660788879838,
|
| 636 |
+
"eval_num_tokens": 1399537.0,
|
| 637 |
+
"eval_runtime": 86.6458,
|
| 638 |
+
"eval_samples_per_second": 15.881,
|
| 639 |
+
"eval_steps_per_second": 1.985,
|
| 640 |
+
"step": 600
|
| 641 |
+
},
|
| 642 |
+
{
|
| 643 |
+
"entropy": 0.5675108034163714,
|
| 644 |
+
"epoch": 1.5429638854296388,
|
| 645 |
+
"grad_norm": 0.837087094783783,
|
| 646 |
+
"learning_rate": 0.0001997694115476612,
|
| 647 |
+
"loss": 0.5099846363067627,
|
| 648 |
+
"mean_token_accuracy": 0.8543680295348167,
|
| 649 |
+
"num_tokens": 1448422.0,
|
| 650 |
+
"step": 620
|
| 651 |
+
},
|
| 652 |
+
{
|
| 653 |
+
"epoch": 1.5429638854296388,
|
| 654 |
+
"eval_entropy": 0.5728072581249614,
|
| 655 |
+
"eval_loss": 0.5445425510406494,
|
| 656 |
+
"eval_mean_token_accuracy": 0.8474342175001321,
|
| 657 |
+
"eval_num_tokens": 1448422.0,
|
| 658 |
+
"eval_runtime": 86.4859,
|
| 659 |
+
"eval_samples_per_second": 15.91,
|
| 660 |
+
"eval_steps_per_second": 1.989,
|
| 661 |
+
"step": 620
|
| 662 |
+
},
|
| 663 |
+
{
|
| 664 |
+
"entropy": 0.5700885068625212,
|
| 665 |
+
"epoch": 1.592777085927771,
|
| 666 |
+
"grad_norm": 0.6598765850067139,
|
| 667 |
+
"learning_rate": 0.000199426677927519,
|
| 668 |
+
"loss": 0.5122694969177246,
|
| 669 |
+
"mean_token_accuracy": 0.8519927568733692,
|
| 670 |
+
"num_tokens": 1495009.0,
|
| 671 |
+
"step": 640
|
| 672 |
+
},
|
| 673 |
+
{
|
| 674 |
+
"epoch": 1.592777085927771,
|
| 675 |
+
"eval_entropy": 0.5476993622128353,
|
| 676 |
+
"eval_loss": 0.5427973866462708,
|
| 677 |
+
"eval_mean_token_accuracy": 0.8478512147138285,
|
| 678 |
+
"eval_num_tokens": 1495009.0,
|
| 679 |
+
"eval_runtime": 86.4172,
|
| 680 |
+
"eval_samples_per_second": 15.923,
|
| 681 |
+
"eval_steps_per_second": 1.99,
|
| 682 |
+
"step": 640
|
| 683 |
+
},
|
| 684 |
+
{
|
| 685 |
+
"entropy": 0.5829229176044464,
|
| 686 |
+
"epoch": 1.6425902864259028,
|
| 687 |
+
"grad_norm": 0.6965194940567017,
|
| 688 |
+
"learning_rate": 0.00019905419277884342,
|
| 689 |
+
"loss": 0.5253659725189209,
|
| 690 |
+
"mean_token_accuracy": 0.8493309423327446,
|
| 691 |
+
"num_tokens": 1536932.0,
|
| 692 |
+
"step": 660
|
| 693 |
+
},
|
| 694 |
+
{
|
| 695 |
+
"epoch": 1.6425902864259028,
|
| 696 |
+
"eval_entropy": 0.5666290084983028,
|
| 697 |
+
"eval_loss": 0.5467478036880493,
|
| 698 |
+
"eval_mean_token_accuracy": 0.8479407703460649,
|
| 699 |
+
"eval_num_tokens": 1536932.0,
|
| 700 |
+
"eval_runtime": 86.4414,
|
| 701 |
+
"eval_samples_per_second": 15.918,
|
| 702 |
+
"eval_steps_per_second": 1.99,
|
| 703 |
+
"step": 660
|
| 704 |
+
},
|
| 705 |
+
{
|
| 706 |
+
"entropy": 0.5498311135917902,
|
| 707 |
+
"epoch": 1.692403486924035,
|
| 708 |
+
"grad_norm": 0.636583685874939,
|
| 709 |
+
"learning_rate": 0.00019865206843807482,
|
| 710 |
+
"loss": 0.49981012344360354,
|
| 711 |
+
"mean_token_accuracy": 0.8560848504304885,
|
| 712 |
+
"num_tokens": 1585718.0,
|
| 713 |
+
"step": 680
|
| 714 |
+
},
|
| 715 |
+
{
|
| 716 |
+
"epoch": 1.692403486924035,
|
| 717 |
+
"eval_entropy": 0.539117265406043,
|
| 718 |
+
"eval_loss": 0.53994220495224,
|
| 719 |
+
"eval_mean_token_accuracy": 0.8488582601380903,
|
| 720 |
+
"eval_num_tokens": 1585718.0,
|
| 721 |
+
"eval_runtime": 86.5296,
|
| 722 |
+
"eval_samples_per_second": 15.902,
|
| 723 |
+
"eval_steps_per_second": 1.988,
|
| 724 |
+
"step": 680
|
| 725 |
+
},
|
| 726 |
+
{
|
| 727 |
+
"entropy": 0.5543891470879316,
|
| 728 |
+
"epoch": 1.7422166874221667,
|
| 729 |
+
"grad_norm": 0.6068442463874817,
|
| 730 |
+
"learning_rate": 0.0001982204261804297,
|
| 731 |
+
"loss": 0.498047399520874,
|
| 732 |
+
"mean_token_accuracy": 0.8554679051041603,
|
| 733 |
+
"num_tokens": 1635718.0,
|
| 734 |
+
"step": 700
|
| 735 |
+
},
|
| 736 |
+
{
|
| 737 |
+
"epoch": 1.7422166874221667,
|
| 738 |
+
"eval_entropy": 0.5703774151760478,
|
| 739 |
+
"eval_loss": 0.5300245881080627,
|
| 740 |
+
"eval_mean_token_accuracy": 0.850798153946566,
|
| 741 |
+
"eval_num_tokens": 1635718.0,
|
| 742 |
+
"eval_runtime": 86.6456,
|
| 743 |
+
"eval_samples_per_second": 15.881,
|
| 744 |
+
"eval_steps_per_second": 1.985,
|
| 745 |
+
"step": 700
|
| 746 |
+
},
|
| 747 |
+
{
|
| 748 |
+
"entropy": 0.546524541825056,
|
| 749 |
+
"epoch": 1.792029887920299,
|
| 750 |
+
"grad_norm": 0.7274155020713806,
|
| 751 |
+
"learning_rate": 0.00019775939618332566,
|
| 752 |
+
"loss": 0.4988589286804199,
|
| 753 |
+
"mean_token_accuracy": 0.853422473371029,
|
| 754 |
+
"num_tokens": 1681291.0,
|
| 755 |
+
"step": 720
|
| 756 |
+
},
|
| 757 |
+
{
|
| 758 |
+
"epoch": 1.792029887920299,
|
| 759 |
+
"eval_entropy": 0.5614905688305234,
|
| 760 |
+
"eval_loss": 0.5350332260131836,
|
| 761 |
+
"eval_mean_token_accuracy": 0.8492204359797544,
|
| 762 |
+
"eval_num_tokens": 1681291.0,
|
| 763 |
+
"eval_runtime": 86.7581,
|
| 764 |
+
"eval_samples_per_second": 15.86,
|
| 765 |
+
"eval_steps_per_second": 1.983,
|
| 766 |
+
"step": 720
|
| 767 |
+
},
|
| 768 |
+
{
|
| 769 |
+
"entropy": 0.5519792139530182,
|
| 770 |
+
"epoch": 1.841843088418431,
|
| 771 |
+
"grad_norm": 0.663466215133667,
|
| 772 |
+
"learning_rate": 0.00019726911748712167,
|
| 773 |
+
"loss": 0.5099314212799072,
|
| 774 |
+
"mean_token_accuracy": 0.848412600159645,
|
| 775 |
+
"num_tokens": 1729102.0,
|
| 776 |
+
"step": 740
|
| 777 |
+
},
|
| 778 |
+
{
|
| 779 |
+
"epoch": 1.841843088418431,
|
| 780 |
+
"eval_entropy": 0.5583519090053647,
|
| 781 |
+
"eval_loss": 0.530483603477478,
|
| 782 |
+
"eval_mean_token_accuracy": 0.8500003374593202,
|
| 783 |
+
"eval_num_tokens": 1729102.0,
|
| 784 |
+
"eval_runtime": 86.3961,
|
| 785 |
+
"eval_samples_per_second": 15.927,
|
| 786 |
+
"eval_steps_per_second": 1.991,
|
| 787 |
+
"step": 740
|
| 788 |
+
},
|
| 789 |
+
{
|
| 790 |
+
"entropy": 0.5454779766499996,
|
| 791 |
+
"epoch": 1.891656288916563,
|
| 792 |
+
"grad_norm": 0.890394926071167,
|
| 793 |
+
"learning_rate": 0.00019674973795318548,
|
| 794 |
+
"loss": 0.4931994915008545,
|
| 795 |
+
"mean_token_accuracy": 0.8540832489728928,
|
| 796 |
+
"num_tokens": 1773578.0,
|
| 797 |
+
"step": 760
|
| 798 |
+
},
|
| 799 |
+
{
|
| 800 |
+
"epoch": 1.891656288916563,
|
| 801 |
+
"eval_entropy": 0.572755502406941,
|
| 802 |
+
"eval_loss": 0.5415747761726379,
|
| 803 |
+
"eval_mean_token_accuracy": 0.8444425803284312,
|
| 804 |
+
"eval_num_tokens": 1773578.0,
|
| 805 |
+
"eval_runtime": 86.4323,
|
| 806 |
+
"eval_samples_per_second": 15.92,
|
| 807 |
+
"eval_steps_per_second": 1.99,
|
| 808 |
+
"step": 760
|
| 809 |
+
},
|
| 810 |
+
{
|
| 811 |
+
"entropy": 0.5392089951783419,
|
| 812 |
+
"epoch": 1.9414694894146949,
|
| 813 |
+
"grad_norm": 0.632411777973175,
|
| 814 |
+
"learning_rate": 0.00019620141421930058,
|
| 815 |
+
"loss": 0.4957888603210449,
|
| 816 |
+
"mean_token_accuracy": 0.8549866065382957,
|
| 817 |
+
"num_tokens": 1821725.0,
|
| 818 |
+
"step": 780
|
| 819 |
+
},
|
| 820 |
+
{
|
| 821 |
+
"epoch": 1.9414694894146949,
|
| 822 |
+
"eval_entropy": 0.540764772961306,
|
| 823 |
+
"eval_loss": 0.5327216386795044,
|
| 824 |
+
"eval_mean_token_accuracy": 0.850631088364956,
|
| 825 |
+
"eval_num_tokens": 1821725.0,
|
| 826 |
+
"eval_runtime": 86.8097,
|
| 827 |
+
"eval_samples_per_second": 15.851,
|
| 828 |
+
"eval_steps_per_second": 1.981,
|
| 829 |
+
"step": 780
|
| 830 |
+
},
|
| 831 |
+
{
|
| 832 |
+
"entropy": 0.5674678739160299,
|
| 833 |
+
"epoch": 1.9912826899128269,
|
| 834 |
+
"grad_norm": 0.6958843469619751,
|
| 835 |
+
"learning_rate": 0.0001956243116524263,
|
| 836 |
+
"loss": 0.504389762878418,
|
| 837 |
+
"mean_token_accuracy": 0.8527948908507824,
|
| 838 |
+
"num_tokens": 1868431.0,
|
| 839 |
+
"step": 800
|
| 840 |
+
},
|
| 841 |
+
{
|
| 842 |
+
"epoch": 1.9912826899128269,
|
| 843 |
+
"eval_entropy": 0.530262403190136,
|
| 844 |
+
"eval_loss": 0.5308871865272522,
|
| 845 |
+
"eval_mean_token_accuracy": 0.8522498046242913,
|
| 846 |
+
"eval_num_tokens": 1868431.0,
|
| 847 |
+
"eval_runtime": 86.7942,
|
| 848 |
+
"eval_samples_per_second": 15.854,
|
| 849 |
+
"eval_steps_per_second": 1.982,
|
| 850 |
+
"step": 800
|
| 851 |
+
},
|
| 852 |
+
{
|
| 853 |
+
"entropy": 0.4742849511213792,
|
| 854 |
+
"epoch": 2.0398505603985058,
|
| 855 |
+
"grad_norm": 0.6941492557525635,
|
| 856 |
+
"learning_rate": 0.00019501860429882556,
|
| 857 |
+
"loss": 0.418599271774292,
|
| 858 |
+
"mean_token_accuracy": 0.8748210859604371,
|
| 859 |
+
"num_tokens": 1915280.0,
|
| 860 |
+
"step": 820
|
| 861 |
+
},
|
| 862 |
+
{
|
| 863 |
+
"epoch": 2.0398505603985058,
|
| 864 |
+
"eval_entropy": 0.504602165069691,
|
| 865 |
+
"eval_loss": 0.542878270149231,
|
| 866 |
+
"eval_mean_token_accuracy": 0.8507604484641275,
|
| 867 |
+
"eval_num_tokens": 1915280.0,
|
| 868 |
+
"eval_runtime": 86.7841,
|
| 869 |
+
"eval_samples_per_second": 15.855,
|
| 870 |
+
"eval_steps_per_second": 1.982,
|
| 871 |
+
"step": 820
|
| 872 |
+
},
|
| 873 |
+
{
|
| 874 |
+
"entropy": 0.45857742577791216,
|
| 875 |
+
"epoch": 2.0896637608966375,
|
| 876 |
+
"grad_norm": 0.5791997909545898,
|
| 877 |
+
"learning_rate": 0.00019438447483157478,
|
| 878 |
+
"loss": 0.399777889251709,
|
| 879 |
+
"mean_token_accuracy": 0.8754058346152306,
|
| 880 |
+
"num_tokens": 1965306.0,
|
| 881 |
+
"step": 840
|
| 882 |
+
},
|
| 883 |
+
{
|
| 884 |
+
"epoch": 2.0896637608966375,
|
| 885 |
+
"eval_entropy": 0.5028848362176918,
|
| 886 |
+
"eval_loss": 0.5356478095054626,
|
| 887 |
+
"eval_mean_token_accuracy": 0.8525635412959165,
|
| 888 |
+
"eval_num_tokens": 1965306.0,
|
| 889 |
+
"eval_runtime": 86.6707,
|
| 890 |
+
"eval_samples_per_second": 15.876,
|
| 891 |
+
"eval_steps_per_second": 1.985,
|
| 892 |
+
"step": 840
|
| 893 |
+
},
|
| 894 |
+
{
|
| 895 |
+
"entropy": 0.4869446292519569,
|
| 896 |
+
"epoch": 2.1394769613947697,
|
| 897 |
+
"grad_norm": 0.6483516693115234,
|
| 898 |
+
"learning_rate": 0.00019372211449547223,
|
| 899 |
+
"loss": 0.40715818405151366,
|
| 900 |
+
"mean_token_accuracy": 0.875113020837307,
|
| 901 |
+
"num_tokens": 2008562.0,
|
| 902 |
+
"step": 860
|
| 903 |
+
},
|
| 904 |
+
{
|
| 905 |
+
"epoch": 2.1394769613947697,
|
| 906 |
+
"eval_entropy": 0.4928991326759028,
|
| 907 |
+
"eval_loss": 0.5419561862945557,
|
| 908 |
+
"eval_mean_token_accuracy": 0.8516040146350861,
|
| 909 |
+
"eval_num_tokens": 2008562.0,
|
| 910 |
+
"eval_runtime": 87.0686,
|
| 911 |
+
"eval_samples_per_second": 15.804,
|
| 912 |
+
"eval_steps_per_second": 1.975,
|
| 913 |
+
"step": 860
|
| 914 |
+
},
|
| 915 |
+
{
|
| 916 |
+
"entropy": 0.45819590501487256,
|
| 917 |
+
"epoch": 2.1892901618929015,
|
| 918 |
+
"grad_norm": 0.6661920547485352,
|
| 919 |
+
"learning_rate": 0.00019303172304936108,
|
| 920 |
+
"loss": 0.39511430263519287,
|
| 921 |
+
"mean_token_accuracy": 0.8780680045485496,
|
| 922 |
+
"num_tokens": 2056474.0,
|
| 923 |
+
"step": 880
|
| 924 |
+
},
|
| 925 |
+
{
|
| 926 |
+
"epoch": 2.1892901618929015,
|
| 927 |
+
"eval_entropy": 0.48602560647698334,
|
| 928 |
+
"eval_loss": 0.5436084866523743,
|
| 929 |
+
"eval_mean_token_accuracy": 0.8500938470973525,
|
| 930 |
+
"eval_num_tokens": 2056474.0,
|
| 931 |
+
"eval_runtime": 86.6809,
|
| 932 |
+
"eval_samples_per_second": 15.874,
|
| 933 |
+
"eval_steps_per_second": 1.984,
|
| 934 |
+
"step": 880
|
| 935 |
+
},
|
| 936 |
+
{
|
| 937 |
+
"entropy": 0.4780638810247183,
|
| 938 |
+
"epoch": 2.2391033623910337,
|
| 939 |
+
"grad_norm": 0.6870484352111816,
|
| 940 |
+
"learning_rate": 0.0001923135087058851,
|
| 941 |
+
"loss": 0.4061615467071533,
|
| 942 |
+
"mean_token_accuracy": 0.8766494184732437,
|
| 943 |
+
"num_tokens": 2103543.0,
|
| 944 |
+
"step": 900
|
| 945 |
+
},
|
| 946 |
+
{
|
| 947 |
+
"epoch": 2.2391033623910337,
|
| 948 |
+
"eval_entropy": 0.48236206035281337,
|
| 949 |
+
"eval_loss": 0.5446090698242188,
|
| 950 |
+
"eval_mean_token_accuracy": 0.8507725513258646,
|
| 951 |
+
"eval_num_tokens": 2103543.0,
|
| 952 |
+
"eval_runtime": 86.7398,
|
| 953 |
+
"eval_samples_per_second": 15.864,
|
| 954 |
+
"eval_steps_per_second": 1.983,
|
| 955 |
+
"step": 900
|
| 956 |
+
},
|
| 957 |
+
{
|
| 958 |
+
"entropy": 0.463029869645834,
|
| 959 |
+
"epoch": 2.2889165628891655,
|
| 960 |
+
"grad_norm": 0.6894590854644775,
|
| 961 |
+
"learning_rate": 0.00019156768806869427,
|
| 962 |
+
"loss": 0.39602413177490237,
|
| 963 |
+
"mean_token_accuracy": 0.876420046389103,
|
| 964 |
+
"num_tokens": 2147861.0,
|
| 965 |
+
"step": 920
|
| 966 |
+
},
|
| 967 |
+
{
|
| 968 |
+
"epoch": 2.2889165628891655,
|
| 969 |
+
"eval_entropy": 0.4904779093556626,
|
| 970 |
+
"eval_loss": 0.5404934287071228,
|
| 971 |
+
"eval_mean_token_accuracy": 0.852238280828609,
|
| 972 |
+
"eval_num_tokens": 2147861.0,
|
| 973 |
+
"eval_runtime": 86.5348,
|
| 974 |
+
"eval_samples_per_second": 15.901,
|
| 975 |
+
"eval_steps_per_second": 1.988,
|
| 976 |
+
"step": 920
|
| 977 |
+
},
|
| 978 |
+
{
|
| 979 |
+
"entropy": 0.4817025110125542,
|
| 980 |
+
"epoch": 2.3387297633872977,
|
| 981 |
+
"grad_norm": 0.7756227254867554,
|
| 982 |
+
"learning_rate": 0.00019079448606712033,
|
| 983 |
+
"loss": 0.4177968502044678,
|
| 984 |
+
"mean_token_accuracy": 0.8712256088852882,
|
| 985 |
+
"num_tokens": 2190561.0,
|
| 986 |
+
"step": 940
|
| 987 |
+
},
|
| 988 |
+
{
|
| 989 |
+
"epoch": 2.3387297633872977,
|
| 990 |
+
"eval_entropy": 0.5153802815218305,
|
| 991 |
+
"eval_loss": 0.5424937605857849,
|
| 992 |
+
"eval_mean_token_accuracy": 0.8506565759348315,
|
| 993 |
+
"eval_num_tokens": 2190561.0,
|
| 994 |
+
"eval_runtime": 86.8973,
|
| 995 |
+
"eval_samples_per_second": 15.835,
|
| 996 |
+
"eval_steps_per_second": 1.979,
|
| 997 |
+
"step": 940
|
| 998 |
+
},
|
| 999 |
+
{
|
| 1000 |
+
"entropy": 0.46456389091908934,
|
| 1001 |
+
"epoch": 2.3885429638854294,
|
| 1002 |
+
"grad_norm": 1.2000319957733154,
|
| 1003 |
+
"learning_rate": 0.00018999413588834105,
|
| 1004 |
+
"loss": 0.4084665775299072,
|
| 1005 |
+
"mean_token_accuracy": 0.8750658087432385,
|
| 1006 |
+
"num_tokens": 2239412.0,
|
| 1007 |
+
"step": 960
|
| 1008 |
+
},
|
| 1009 |
+
{
|
| 1010 |
+
"epoch": 2.3885429638854294,
|
| 1011 |
+
"eval_entropy": 0.4849439303195754,
|
| 1012 |
+
"eval_loss": 0.545662522315979,
|
| 1013 |
+
"eval_mean_token_accuracy": 0.8491013112456299,
|
| 1014 |
+
"eval_num_tokens": 2239412.0,
|
| 1015 |
+
"eval_runtime": 86.9049,
|
| 1016 |
+
"eval_samples_per_second": 15.833,
|
| 1017 |
+
"eval_steps_per_second": 1.979,
|
| 1018 |
+
"step": 960
|
| 1019 |
+
},
|
| 1020 |
+
{
|
| 1021 |
+
"entropy": 0.4857471022754908,
|
| 1022 |
+
"epoch": 2.4383561643835616,
|
| 1023 |
+
"grad_norm": 0.9696341753005981,
|
| 1024 |
+
"learning_rate": 0.0001891668789070541,
|
| 1025 |
+
"loss": 0.4149796962738037,
|
| 1026 |
+
"mean_token_accuracy": 0.8704176343977451,
|
| 1027 |
+
"num_tokens": 2286283.0,
|
| 1028 |
+
"step": 980
|
| 1029 |
+
},
|
| 1030 |
+
{
|
| 1031 |
+
"epoch": 2.4383561643835616,
|
| 1032 |
+
"eval_entropy": 0.4872790058684904,
|
| 1033 |
+
"eval_loss": 0.5412707924842834,
|
| 1034 |
+
"eval_mean_token_accuracy": 0.8509329602468846,
|
| 1035 |
+
"eval_num_tokens": 2286283.0,
|
| 1036 |
+
"eval_runtime": 86.7846,
|
| 1037 |
+
"eval_samples_per_second": 15.855,
|
| 1038 |
+
"eval_steps_per_second": 1.982,
|
| 1039 |
+
"step": 980
|
| 1040 |
+
},
|
| 1041 |
+
{
|
| 1042 |
+
"entropy": 0.4727417893707752,
|
| 1043 |
+
"epoch": 2.488169364881694,
|
| 1044 |
+
"grad_norm": 0.7852500677108765,
|
| 1045 |
+
"learning_rate": 0.0001883129646126818,
|
| 1046 |
+
"loss": 0.4142886161804199,
|
| 1047 |
+
"mean_token_accuracy": 0.8712429471313954,
|
| 1048 |
+
"num_tokens": 2333733.0,
|
| 1049 |
+
"step": 1000
|
| 1050 |
+
},
|
| 1051 |
+
{
|
| 1052 |
+
"epoch": 2.488169364881694,
|
| 1053 |
+
"eval_entropy": 0.5386548059624295,
|
| 1054 |
+
"eval_loss": 0.536101222038269,
|
| 1055 |
+
"eval_mean_token_accuracy": 0.8499491239009902,
|
| 1056 |
+
"eval_num_tokens": 2333733.0,
|
| 1057 |
+
"eval_runtime": 86.9501,
|
| 1058 |
+
"eval_samples_per_second": 15.825,
|
| 1059 |
+
"eval_steps_per_second": 1.978,
|
| 1060 |
+
"step": 1000
|
| 1061 |
+
},
|
| 1062 |
+
{
|
| 1063 |
+
"entropy": 0.4673406321555376,
|
| 1064 |
+
"epoch": 2.5379825653798256,
|
| 1065 |
+
"grad_norm": 0.7133921384811401,
|
| 1066 |
+
"learning_rate": 0.0001874326505341286,
|
| 1067 |
+
"loss": 0.40857529640197754,
|
| 1068 |
+
"mean_token_accuracy": 0.8747925907373428,
|
| 1069 |
+
"num_tokens": 2384270.0,
|
| 1070 |
+
"step": 1020
|
| 1071 |
+
},
|
| 1072 |
+
{
|
| 1073 |
+
"epoch": 2.5379825653798256,
|
| 1074 |
+
"eval_entropy": 0.495788364909416,
|
| 1075 |
+
"eval_loss": 0.5418923497200012,
|
| 1076 |
+
"eval_mean_token_accuracy": 0.851321972040243,
|
| 1077 |
+
"eval_num_tokens": 2384270.0,
|
| 1078 |
+
"eval_runtime": 86.7154,
|
| 1079 |
+
"eval_samples_per_second": 15.868,
|
| 1080 |
+
"eval_steps_per_second": 1.983,
|
| 1081 |
+
"step": 1020
|
| 1082 |
+
},
|
| 1083 |
+
{
|
| 1084 |
+
"entropy": 0.47599745728075504,
|
| 1085 |
+
"epoch": 2.587795765877958,
|
| 1086 |
+
"grad_norm": 0.8202953338623047,
|
| 1087 |
+
"learning_rate": 0.0001865262021621137,
|
| 1088 |
+
"loss": 0.40998234748840334,
|
| 1089 |
+
"mean_token_accuracy": 0.8758242674171924,
|
| 1090 |
+
"num_tokens": 2428036.0,
|
| 1091 |
+
"step": 1040
|
| 1092 |
+
},
|
| 1093 |
+
{
|
| 1094 |
+
"epoch": 2.587795765877958,
|
| 1095 |
+
"eval_entropy": 0.4887966953737791,
|
| 1096 |
+
"eval_loss": 0.5408804416656494,
|
| 1097 |
+
"eval_mean_token_accuracy": 0.8512661065473113,
|
| 1098 |
+
"eval_num_tokens": 2428036.0,
|
| 1099 |
+
"eval_runtime": 86.7869,
|
| 1100 |
+
"eval_samples_per_second": 15.855,
|
| 1101 |
+
"eval_steps_per_second": 1.982,
|
| 1102 |
+
"step": 1040
|
| 1103 |
+
},
|
| 1104 |
+
{
|
| 1105 |
+
"entropy": 0.4824396539479494,
|
| 1106 |
+
"epoch": 2.6376089663760895,
|
| 1107 |
+
"grad_norm": 0.6507360935211182,
|
| 1108 |
+
"learning_rate": 0.00018559389286910275,
|
| 1109 |
+
"loss": 0.4165764808654785,
|
| 1110 |
+
"mean_token_accuracy": 0.8722914069890976,
|
| 1111 |
+
"num_tokens": 2476815.0,
|
| 1112 |
+
"step": 1060
|
| 1113 |
+
},
|
| 1114 |
+
{
|
| 1115 |
+
"epoch": 2.6376089663760895,
|
| 1116 |
+
"eval_entropy": 0.4793398808254752,
|
| 1117 |
+
"eval_loss": 0.5326959490776062,
|
| 1118 |
+
"eval_mean_token_accuracy": 0.8534493650807891,
|
| 1119 |
+
"eval_num_tokens": 2476815.0,
|
| 1120 |
+
"eval_runtime": 86.9559,
|
| 1121 |
+
"eval_samples_per_second": 15.824,
|
| 1122 |
+
"eval_steps_per_second": 1.978,
|
| 1123 |
+
"step": 1060
|
| 1124 |
+
}
|
| 1125 |
+
],
|
| 1126 |
+
"logging_steps": 20,
|
| 1127 |
+
"max_steps": 4020,
|
| 1128 |
+
"num_input_tokens_seen": 0,
|
| 1129 |
+
"num_train_epochs": 10,
|
| 1130 |
+
"save_steps": 20,
|
| 1131 |
+
"stateful_callbacks": {
|
| 1132 |
+
"TrainerControl": {
|
| 1133 |
+
"args": {
|
| 1134 |
+
"should_epoch_stop": false,
|
| 1135 |
+
"should_evaluate": false,
|
| 1136 |
+
"should_log": false,
|
| 1137 |
+
"should_save": true,
|
| 1138 |
+
"should_training_stop": false
|
| 1139 |
+
},
|
| 1140 |
+
"attributes": {}
|
| 1141 |
+
}
|
| 1142 |
+
},
|
| 1143 |
+
"total_flos": 1.045743734380032e+17,
|
| 1144 |
+
"train_batch_size": 4,
|
| 1145 |
+
"trial_name": null,
|
| 1146 |
+
"trial_params": null
|
| 1147 |
+
}
|
overgeneralisation_original_Swedish/Qwen3.5-4B-Base_overgeneralisation_splits_original_features_train_overgeneralisation_splits_original_features_test1/checkpoint-1080/README.md
ADDED
|
@@ -0,0 +1,209 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
---
|
| 2 |
+
base_model: Qwen/Qwen3.5-4B-Base
|
| 3 |
+
library_name: peft
|
| 4 |
+
pipeline_tag: text-generation
|
| 5 |
+
tags:
|
| 6 |
+
- base_model:adapter:Qwen/Qwen3.5-4B-Base
|
| 7 |
+
- lora
|
| 8 |
+
- sft
|
| 9 |
+
- transformers
|
| 10 |
+
- trl
|
| 11 |
+
---
|
| 12 |
+
|
| 13 |
+
# Model Card for Model ID
|
| 14 |
+
|
| 15 |
+
<!-- Provide a quick summary of what the model is/does. -->
|
| 16 |
+
|
| 17 |
+
|
| 18 |
+
|
| 19 |
+
## Model Details
|
| 20 |
+
|
| 21 |
+
### Model Description
|
| 22 |
+
|
| 23 |
+
<!-- Provide a longer summary of what this model is. -->
|
| 24 |
+
|
| 25 |
+
|
| 26 |
+
|
| 27 |
+
- **Developed by:** [More Information Needed]
|
| 28 |
+
- **Funded by [optional]:** [More Information Needed]
|
| 29 |
+
- **Shared by [optional]:** [More Information Needed]
|
| 30 |
+
- **Model type:** [More Information Needed]
|
| 31 |
+
- **Language(s) (NLP):** [More Information Needed]
|
| 32 |
+
- **License:** [More Information Needed]
|
| 33 |
+
- **Finetuned from model [optional]:** [More Information Needed]
|
| 34 |
+
|
| 35 |
+
### Model Sources [optional]
|
| 36 |
+
|
| 37 |
+
<!-- Provide the basic links for the model. -->
|
| 38 |
+
|
| 39 |
+
- **Repository:** [More Information Needed]
|
| 40 |
+
- **Paper [optional]:** [More Information Needed]
|
| 41 |
+
- **Demo [optional]:** [More Information Needed]
|
| 42 |
+
|
| 43 |
+
## Uses
|
| 44 |
+
|
| 45 |
+
<!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
|
| 46 |
+
|
| 47 |
+
### Direct Use
|
| 48 |
+
|
| 49 |
+
<!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
|
| 50 |
+
|
| 51 |
+
[More Information Needed]
|
| 52 |
+
|
| 53 |
+
### Downstream Use [optional]
|
| 54 |
+
|
| 55 |
+
<!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
|
| 56 |
+
|
| 57 |
+
[More Information Needed]
|
| 58 |
+
|
| 59 |
+
### Out-of-Scope Use
|
| 60 |
+
|
| 61 |
+
<!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
|
| 62 |
+
|
| 63 |
+
[More Information Needed]
|
| 64 |
+
|
| 65 |
+
## Bias, Risks, and Limitations
|
| 66 |
+
|
| 67 |
+
<!-- This section is meant to convey both technical and sociotechnical limitations. -->
|
| 68 |
+
|
| 69 |
+
[More Information Needed]
|
| 70 |
+
|
| 71 |
+
### Recommendations
|
| 72 |
+
|
| 73 |
+
<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
|
| 74 |
+
|
| 75 |
+
Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
|
| 76 |
+
|
| 77 |
+
## How to Get Started with the Model
|
| 78 |
+
|
| 79 |
+
Use the code below to get started with the model.
|
| 80 |
+
|
| 81 |
+
[More Information Needed]
|
| 82 |
+
|
| 83 |
+
## Training Details
|
| 84 |
+
|
| 85 |
+
### Training Data
|
| 86 |
+
|
| 87 |
+
<!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
|
| 88 |
+
|
| 89 |
+
[More Information Needed]
|
| 90 |
+
|
| 91 |
+
### Training Procedure
|
| 92 |
+
|
| 93 |
+
<!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
|
| 94 |
+
|
| 95 |
+
#### Preprocessing [optional]
|
| 96 |
+
|
| 97 |
+
[More Information Needed]
|
| 98 |
+
|
| 99 |
+
|
| 100 |
+
#### Training Hyperparameters
|
| 101 |
+
|
| 102 |
+
- **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
|
| 103 |
+
|
| 104 |
+
#### Speeds, Sizes, Times [optional]
|
| 105 |
+
|
| 106 |
+
<!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
|
| 107 |
+
|
| 108 |
+
[More Information Needed]
|
| 109 |
+
|
| 110 |
+
## Evaluation
|
| 111 |
+
|
| 112 |
+
<!-- This section describes the evaluation protocols and provides the results. -->
|
| 113 |
+
|
| 114 |
+
### Testing Data, Factors & Metrics
|
| 115 |
+
|
| 116 |
+
#### Testing Data
|
| 117 |
+
|
| 118 |
+
<!-- This should link to a Dataset Card if possible. -->
|
| 119 |
+
|
| 120 |
+
[More Information Needed]
|
| 121 |
+
|
| 122 |
+
#### Factors
|
| 123 |
+
|
| 124 |
+
<!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
|
| 125 |
+
|
| 126 |
+
[More Information Needed]
|
| 127 |
+
|
| 128 |
+
#### Metrics
|
| 129 |
+
|
| 130 |
+
<!-- These are the evaluation metrics being used, ideally with a description of why. -->
|
| 131 |
+
|
| 132 |
+
[More Information Needed]
|
| 133 |
+
|
| 134 |
+
### Results
|
| 135 |
+
|
| 136 |
+
[More Information Needed]
|
| 137 |
+
|
| 138 |
+
#### Summary
|
| 139 |
+
|
| 140 |
+
|
| 141 |
+
|
| 142 |
+
## Model Examination [optional]
|
| 143 |
+
|
| 144 |
+
<!-- Relevant interpretability work for the model goes here -->
|
| 145 |
+
|
| 146 |
+
[More Information Needed]
|
| 147 |
+
|
| 148 |
+
## Environmental Impact
|
| 149 |
+
|
| 150 |
+
<!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
|
| 151 |
+
|
| 152 |
+
Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
|
| 153 |
+
|
| 154 |
+
- **Hardware Type:** [More Information Needed]
|
| 155 |
+
- **Hours used:** [More Information Needed]
|
| 156 |
+
- **Cloud Provider:** [More Information Needed]
|
| 157 |
+
- **Compute Region:** [More Information Needed]
|
| 158 |
+
- **Carbon Emitted:** [More Information Needed]
|
| 159 |
+
|
| 160 |
+
## Technical Specifications [optional]
|
| 161 |
+
|
| 162 |
+
### Model Architecture and Objective
|
| 163 |
+
|
| 164 |
+
[More Information Needed]
|
| 165 |
+
|
| 166 |
+
### Compute Infrastructure
|
| 167 |
+
|
| 168 |
+
[More Information Needed]
|
| 169 |
+
|
| 170 |
+
#### Hardware
|
| 171 |
+
|
| 172 |
+
[More Information Needed]
|
| 173 |
+
|
| 174 |
+
#### Software
|
| 175 |
+
|
| 176 |
+
[More Information Needed]
|
| 177 |
+
|
| 178 |
+
## Citation [optional]
|
| 179 |
+
|
| 180 |
+
<!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
|
| 181 |
+
|
| 182 |
+
**BibTeX:**
|
| 183 |
+
|
| 184 |
+
[More Information Needed]
|
| 185 |
+
|
| 186 |
+
**APA:**
|
| 187 |
+
|
| 188 |
+
[More Information Needed]
|
| 189 |
+
|
| 190 |
+
## Glossary [optional]
|
| 191 |
+
|
| 192 |
+
<!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
|
| 193 |
+
|
| 194 |
+
[More Information Needed]
|
| 195 |
+
|
| 196 |
+
## More Information [optional]
|
| 197 |
+
|
| 198 |
+
[More Information Needed]
|
| 199 |
+
|
| 200 |
+
## Model Card Authors [optional]
|
| 201 |
+
|
| 202 |
+
[More Information Needed]
|
| 203 |
+
|
| 204 |
+
## Model Card Contact
|
| 205 |
+
|
| 206 |
+
[More Information Needed]
|
| 207 |
+
### Framework versions
|
| 208 |
+
|
| 209 |
+
- PEFT 0.18.1
|
overgeneralisation_original_Swedish/Qwen3.5-4B-Base_overgeneralisation_splits_original_features_train_overgeneralisation_splits_original_features_test1/checkpoint-1080/adapter_config.json
ADDED
|
@@ -0,0 +1,46 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
{
|
| 2 |
+
"alora_invocation_tokens": null,
|
| 3 |
+
"alpha_pattern": {},
|
| 4 |
+
"arrow_config": null,
|
| 5 |
+
"auto_mapping": null,
|
| 6 |
+
"base_model_name_or_path": "Qwen/Qwen3.5-4B-Base",
|
| 7 |
+
"bias": "none",
|
| 8 |
+
"corda_config": null,
|
| 9 |
+
"ensure_weight_tying": false,
|
| 10 |
+
"eva_config": null,
|
| 11 |
+
"exclude_modules": null,
|
| 12 |
+
"fan_in_fan_out": false,
|
| 13 |
+
"inference_mode": true,
|
| 14 |
+
"init_lora_weights": true,
|
| 15 |
+
"layer_replication": null,
|
| 16 |
+
"layers_pattern": null,
|
| 17 |
+
"layers_to_transform": null,
|
| 18 |
+
"loftq_config": {},
|
| 19 |
+
"lora_alpha": 256,
|
| 20 |
+
"lora_bias": false,
|
| 21 |
+
"lora_dropout": 0.0005183818805460705,
|
| 22 |
+
"megatron_config": null,
|
| 23 |
+
"megatron_core": "megatron.core",
|
| 24 |
+
"modules_to_save": null,
|
| 25 |
+
"peft_type": "LORA",
|
| 26 |
+
"peft_version": "0.18.1",
|
| 27 |
+
"qalora_group_size": 16,
|
| 28 |
+
"r": 128,
|
| 29 |
+
"rank_pattern": {},
|
| 30 |
+
"revision": null,
|
| 31 |
+
"target_modules": [
|
| 32 |
+
"up_proj",
|
| 33 |
+
"q_proj",
|
| 34 |
+
"o_proj",
|
| 35 |
+
"v_proj",
|
| 36 |
+
"k_proj",
|
| 37 |
+
"gate_proj",
|
| 38 |
+
"down_proj"
|
| 39 |
+
],
|
| 40 |
+
"target_parameters": null,
|
| 41 |
+
"task_type": "CAUSAL_LM",
|
| 42 |
+
"trainable_token_indices": null,
|
| 43 |
+
"use_dora": false,
|
| 44 |
+
"use_qalora": false,
|
| 45 |
+
"use_rslora": false
|
| 46 |
+
}
|
overgeneralisation_original_Swedish/Qwen3.5-4B-Base_overgeneralisation_splits_original_features_train_overgeneralisation_splits_original_features_test1/checkpoint-1080/chat_template.jinja
ADDED
|
@@ -0,0 +1,154 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
{%- set image_count = namespace(value=0) %}
|
| 2 |
+
{%- set video_count = namespace(value=0) %}
|
| 3 |
+
{%- macro render_content(content, do_vision_count, is_system_content=false) %}
|
| 4 |
+
{%- if content is string %}
|
| 5 |
+
{{- content }}
|
| 6 |
+
{%- elif content is iterable and content is not mapping %}
|
| 7 |
+
{%- for item in content %}
|
| 8 |
+
{%- if 'image' in item or 'image_url' in item or item.type == 'image' %}
|
| 9 |
+
{%- if is_system_content %}
|
| 10 |
+
{{- raise_exception('System message cannot contain images.') }}
|
| 11 |
+
{%- endif %}
|
| 12 |
+
{%- if do_vision_count %}
|
| 13 |
+
{%- set image_count.value = image_count.value + 1 %}
|
| 14 |
+
{%- endif %}
|
| 15 |
+
{%- if add_vision_id %}
|
| 16 |
+
{{- 'Picture ' ~ image_count.value ~ ': ' }}
|
| 17 |
+
{%- endif %}
|
| 18 |
+
{{- '<|vision_start|><|image_pad|><|vision_end|>' }}
|
| 19 |
+
{%- elif 'video' in item or item.type == 'video' %}
|
| 20 |
+
{%- if is_system_content %}
|
| 21 |
+
{{- raise_exception('System message cannot contain videos.') }}
|
| 22 |
+
{%- endif %}
|
| 23 |
+
{%- if do_vision_count %}
|
| 24 |
+
{%- set video_count.value = video_count.value + 1 %}
|
| 25 |
+
{%- endif %}
|
| 26 |
+
{%- if add_vision_id %}
|
| 27 |
+
{{- 'Video ' ~ video_count.value ~ ': ' }}
|
| 28 |
+
{%- endif %}
|
| 29 |
+
{{- '<|vision_start|><|video_pad|><|vision_end|>' }}
|
| 30 |
+
{%- elif 'text' in item %}
|
| 31 |
+
{{- item.text }}
|
| 32 |
+
{%- else %}
|
| 33 |
+
{{- raise_exception('Unexpected item type in content.') }}
|
| 34 |
+
{%- endif %}
|
| 35 |
+
{%- endfor %}
|
| 36 |
+
{%- elif content is none or content is undefined %}
|
| 37 |
+
{{- '' }}
|
| 38 |
+
{%- else %}
|
| 39 |
+
{{- raise_exception('Unexpected content type.') }}
|
| 40 |
+
{%- endif %}
|
| 41 |
+
{%- endmacro %}
|
| 42 |
+
{%- if not messages %}
|
| 43 |
+
{{- raise_exception('No messages provided.') }}
|
| 44 |
+
{%- endif %}
|
| 45 |
+
{%- if tools and tools is iterable and tools is not mapping %}
|
| 46 |
+
{{- '<|im_start|>system\n' }}
|
| 47 |
+
{{- "# Tools\n\nYou have access to the following functions:\n\n<tools>" }}
|
| 48 |
+
{%- for tool in tools %}
|
| 49 |
+
{{- "\n" }}
|
| 50 |
+
{{- tool | tojson }}
|
| 51 |
+
{%- endfor %}
|
| 52 |
+
{{- "\n</tools>" }}
|
| 53 |
+
{{- '\n\nIf you choose to call a function ONLY reply in the following format with NO suffix:\n\n<tool_call>\n<function=example_function_name>\n<parameter=example_parameter_1>\nvalue_1\n</parameter>\n<parameter=example_parameter_2>\nThis is the value for the second parameter\nthat can span\nmultiple lines\n</parameter>\n</function>\n</tool_call>\n\n<IMPORTANT>\nReminder:\n- Function calls MUST follow the specified format: an inner <function=...></function> block must be nested within <tool_call></tool_call> XML tags\n- Required parameters MUST be specified\n- You may provide optional reasoning for your function call in natural language BEFORE the function call, but NOT after\n- If there is no function call available, answer the question like normal with your current knowledge and do not tell the user about function calls\n</IMPORTANT>' }}
|
| 54 |
+
{%- if messages[0].role == 'system' %}
|
| 55 |
+
{%- set content = render_content(messages[0].content, false, true)|trim %}
|
| 56 |
+
{%- if content %}
|
| 57 |
+
{{- '\n\n' + content }}
|
| 58 |
+
{%- endif %}
|
| 59 |
+
{%- endif %}
|
| 60 |
+
{{- '<|im_end|>\n' }}
|
| 61 |
+
{%- else %}
|
| 62 |
+
{%- if messages[0].role == 'system' %}
|
| 63 |
+
{%- set content = render_content(messages[0].content, false, true)|trim %}
|
| 64 |
+
{{- '<|im_start|>system\n' + content + '<|im_end|>\n' }}
|
| 65 |
+
{%- endif %}
|
| 66 |
+
{%- endif %}
|
| 67 |
+
{%- set ns = namespace(multi_step_tool=true, last_query_index=messages|length - 1) %}
|
| 68 |
+
{%- for message in messages[::-1] %}
|
| 69 |
+
{%- set index = (messages|length - 1) - loop.index0 %}
|
| 70 |
+
{%- if ns.multi_step_tool and message.role == "user" %}
|
| 71 |
+
{%- set content = render_content(message.content, false)|trim %}
|
| 72 |
+
{%- if not(content.startswith('<tool_response>') and content.endswith('</tool_response>')) %}
|
| 73 |
+
{%- set ns.multi_step_tool = false %}
|
| 74 |
+
{%- set ns.last_query_index = index %}
|
| 75 |
+
{%- endif %}
|
| 76 |
+
{%- endif %}
|
| 77 |
+
{%- endfor %}
|
| 78 |
+
{%- if ns.multi_step_tool %}
|
| 79 |
+
{{- raise_exception('No user query found in messages.') }}
|
| 80 |
+
{%- endif %}
|
| 81 |
+
{%- for message in messages %}
|
| 82 |
+
{%- set content = render_content(message.content, true)|trim %}
|
| 83 |
+
{%- if message.role == "system" %}
|
| 84 |
+
{%- if not loop.first %}
|
| 85 |
+
{{- raise_exception('System message must be at the beginning.') }}
|
| 86 |
+
{%- endif %}
|
| 87 |
+
{%- elif message.role == "user" %}
|
| 88 |
+
{{- '<|im_start|>' + message.role + '\n' + content + '<|im_end|>' + '\n' }}
|
| 89 |
+
{%- elif message.role == "assistant" %}
|
| 90 |
+
{%- set reasoning_content = '' %}
|
| 91 |
+
{%- if message.reasoning_content is string %}
|
| 92 |
+
{%- set reasoning_content = message.reasoning_content %}
|
| 93 |
+
{%- else %}
|
| 94 |
+
{%- if '</think>' in content %}
|
| 95 |
+
{%- set reasoning_content = content.split('</think>')[0].rstrip('\n').split('<think>')[-1].lstrip('\n') %}
|
| 96 |
+
{%- set content = content.split('</think>')[-1].lstrip('\n') %}
|
| 97 |
+
{%- endif %}
|
| 98 |
+
{%- endif %}
|
| 99 |
+
{%- set reasoning_content = reasoning_content|trim %}
|
| 100 |
+
{%- if loop.index0 > ns.last_query_index %}
|
| 101 |
+
{{- '<|im_start|>' + message.role + '\n<think>\n' + reasoning_content + '\n</think>\n\n' + content }}
|
| 102 |
+
{%- else %}
|
| 103 |
+
{{- '<|im_start|>' + message.role + '\n' + content }}
|
| 104 |
+
{%- endif %}
|
| 105 |
+
{%- if message.tool_calls and message.tool_calls is iterable and message.tool_calls is not mapping %}
|
| 106 |
+
{%- for tool_call in message.tool_calls %}
|
| 107 |
+
{%- if tool_call.function is defined %}
|
| 108 |
+
{%- set tool_call = tool_call.function %}
|
| 109 |
+
{%- endif %}
|
| 110 |
+
{%- if loop.first %}
|
| 111 |
+
{%- if content|trim %}
|
| 112 |
+
{{- '\n\n<tool_call>\n<function=' + tool_call.name + '>\n' }}
|
| 113 |
+
{%- else %}
|
| 114 |
+
{{- '<tool_call>\n<function=' + tool_call.name + '>\n' }}
|
| 115 |
+
{%- endif %}
|
| 116 |
+
{%- else %}
|
| 117 |
+
{{- '\n<tool_call>\n<function=' + tool_call.name + '>\n' }}
|
| 118 |
+
{%- endif %}
|
| 119 |
+
{%- if tool_call.arguments is defined %}
|
| 120 |
+
{%- for args_name, args_value in tool_call.arguments|items %}
|
| 121 |
+
{{- '<parameter=' + args_name + '>\n' }}
|
| 122 |
+
{%- set args_value = args_value | tojson | safe if args_value is mapping or (args_value is sequence and args_value is not string) else args_value | string %}
|
| 123 |
+
{{- args_value }}
|
| 124 |
+
{{- '\n</parameter>\n' }}
|
| 125 |
+
{%- endfor %}
|
| 126 |
+
{%- endif %}
|
| 127 |
+
{{- '</function>\n</tool_call>' }}
|
| 128 |
+
{%- endfor %}
|
| 129 |
+
{%- endif %}
|
| 130 |
+
{{- '<|im_end|>\n' }}
|
| 131 |
+
{%- elif message.role == "tool" %}
|
| 132 |
+
{%- if loop.previtem and loop.previtem.role != "tool" %}
|
| 133 |
+
{{- '<|im_start|>user' }}
|
| 134 |
+
{%- endif %}
|
| 135 |
+
{{- '\n<tool_response>\n' }}
|
| 136 |
+
{{- content }}
|
| 137 |
+
{{- '\n</tool_response>' }}
|
| 138 |
+
{%- if not loop.last and loop.nextitem.role != "tool" %}
|
| 139 |
+
{{- '<|im_end|>\n' }}
|
| 140 |
+
{%- elif loop.last %}
|
| 141 |
+
{{- '<|im_end|>\n' }}
|
| 142 |
+
{%- endif %}
|
| 143 |
+
{%- else %}
|
| 144 |
+
{{- raise_exception('Unexpected message role.') }}
|
| 145 |
+
{%- endif %}
|
| 146 |
+
{%- endfor %}
|
| 147 |
+
{%- if add_generation_prompt %}
|
| 148 |
+
{{- '<|im_start|>assistant\n' }}
|
| 149 |
+
{%- if enable_thinking is defined and enable_thinking is false %}
|
| 150 |
+
{{- '<think>\n\n</think>\n\n' }}
|
| 151 |
+
{%- else %}
|
| 152 |
+
{{- '<think>\n' }}
|
| 153 |
+
{%- endif %}
|
| 154 |
+
{%- endif %}
|
overgeneralisation_original_Swedish/Qwen3.5-4B-Base_overgeneralisation_splits_original_features_train_overgeneralisation_splits_original_features_test1/checkpoint-1080/tokenizer_config.json
ADDED
|
@@ -0,0 +1,31 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
{
|
| 2 |
+
"add_prefix_space": false,
|
| 3 |
+
"audio_bos_token": "<|audio_start|>",
|
| 4 |
+
"audio_eos_token": "<|audio_end|>",
|
| 5 |
+
"audio_token": "<|audio_pad|>",
|
| 6 |
+
"backend": "tokenizers",
|
| 7 |
+
"bos_token": null,
|
| 8 |
+
"clean_up_tokenization_spaces": false,
|
| 9 |
+
"eos_token": "<|endoftext|>",
|
| 10 |
+
"errors": "replace",
|
| 11 |
+
"image_token": "<|image_pad|>",
|
| 12 |
+
"is_local": false,
|
| 13 |
+
"model_max_length": 262144,
|
| 14 |
+
"model_specific_special_tokens": {
|
| 15 |
+
"audio_bos_token": "<|audio_start|>",
|
| 16 |
+
"audio_eos_token": "<|audio_end|>",
|
| 17 |
+
"audio_token": "<|audio_pad|>",
|
| 18 |
+
"image_token": "<|image_pad|>",
|
| 19 |
+
"video_token": "<|video_pad|>",
|
| 20 |
+
"vision_bos_token": "<|vision_start|>",
|
| 21 |
+
"vision_eos_token": "<|vision_end|>"
|
| 22 |
+
},
|
| 23 |
+
"pad_token": "<|endoftext|>",
|
| 24 |
+
"pretokenize_regex": "(?i:'s|'t|'re|'ve|'m|'ll|'d)|[^\\r\\n\\p{L}\\p{N}]?[\\p{L}\\p{M}]+|\\p{N}| ?[^\\s\\p{L}\\p{M}\\p{N}]+[\\r\\n]*|\\s*[\\r\\n]+|\\s+(?!\\S)|\\s+",
|
| 25 |
+
"split_special_tokens": false,
|
| 26 |
+
"tokenizer_class": "TokenizersBackend",
|
| 27 |
+
"unk_token": null,
|
| 28 |
+
"video_token": "<|video_pad|>",
|
| 29 |
+
"vision_bos_token": "<|vision_start|>",
|
| 30 |
+
"vision_eos_token": "<|vision_end|>"
|
| 31 |
+
}
|
overgeneralisation_original_Swedish/Qwen3.5-4B-Base_overgeneralisation_splits_original_features_train_overgeneralisation_splits_original_features_test1/checkpoint-1080/trainer_state.json
ADDED
|
@@ -0,0 +1,1168 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
{
|
| 2 |
+
"best_global_step": null,
|
| 3 |
+
"best_metric": null,
|
| 4 |
+
"best_model_checkpoint": null,
|
| 5 |
+
"epoch": 2.6874221668742218,
|
| 6 |
+
"eval_steps": 20,
|
| 7 |
+
"global_step": 1080,
|
| 8 |
+
"is_hyper_param_search": false,
|
| 9 |
+
"is_local_process_zero": true,
|
| 10 |
+
"is_world_process_zero": true,
|
| 11 |
+
"log_history": [
|
| 12 |
+
{
|
| 13 |
+
"entropy": 1.9784346982836722,
|
| 14 |
+
"epoch": 0.049813200498132,
|
| 15 |
+
"grad_norm": 3.0229668617248535,
|
| 16 |
+
"learning_rate": 9.526142962415369e-06,
|
| 17 |
+
"loss": 1.7360023498535155,
|
| 18 |
+
"mean_token_accuracy": 0.6449888605624438,
|
| 19 |
+
"num_tokens": 46794.0,
|
| 20 |
+
"step": 20
|
| 21 |
+
},
|
| 22 |
+
{
|
| 23 |
+
"epoch": 0.049813200498132,
|
| 24 |
+
"eval_entropy": 1.41506897571475,
|
| 25 |
+
"eval_loss": 1.1876318454742432,
|
| 26 |
+
"eval_mean_token_accuracy": 0.734131895525511,
|
| 27 |
+
"eval_num_tokens": 46794.0,
|
| 28 |
+
"eval_runtime": 87.8071,
|
| 29 |
+
"eval_samples_per_second": 15.671,
|
| 30 |
+
"eval_steps_per_second": 1.959,
|
| 31 |
+
"step": 20
|
| 32 |
+
},
|
| 33 |
+
{
|
| 34 |
+
"entropy": 1.049924298375845,
|
| 35 |
+
"epoch": 0.099626400996264,
|
| 36 |
+
"grad_norm": 1.5795097351074219,
|
| 37 |
+
"learning_rate": 1.9553661870221022e-05,
|
| 38 |
+
"loss": 0.8944448471069336,
|
| 39 |
+
"mean_token_accuracy": 0.7748479396104813,
|
| 40 |
+
"num_tokens": 90754.0,
|
| 41 |
+
"step": 40
|
| 42 |
+
},
|
| 43 |
+
{
|
| 44 |
+
"epoch": 0.099626400996264,
|
| 45 |
+
"eval_entropy": 0.7996658658565476,
|
| 46 |
+
"eval_loss": 0.7202735543251038,
|
| 47 |
+
"eval_mean_token_accuracy": 0.8070558306089667,
|
| 48 |
+
"eval_num_tokens": 90754.0,
|
| 49 |
+
"eval_runtime": 86.9199,
|
| 50 |
+
"eval_samples_per_second": 15.831,
|
| 51 |
+
"eval_steps_per_second": 1.979,
|
| 52 |
+
"step": 40
|
| 53 |
+
},
|
| 54 |
+
{
|
| 55 |
+
"entropy": 0.7734908878803253,
|
| 56 |
+
"epoch": 0.149439601494396,
|
| 57 |
+
"grad_norm": 1.3136248588562012,
|
| 58 |
+
"learning_rate": 2.9581180778026673e-05,
|
| 59 |
+
"loss": 0.6780608654022217,
|
| 60 |
+
"mean_token_accuracy": 0.8168170280754566,
|
| 61 |
+
"num_tokens": 137472.0,
|
| 62 |
+
"step": 60
|
| 63 |
+
},
|
| 64 |
+
{
|
| 65 |
+
"epoch": 0.149439601494396,
|
| 66 |
+
"eval_entropy": 0.7119324009778888,
|
| 67 |
+
"eval_loss": 0.6554311513900757,
|
| 68 |
+
"eval_mean_token_accuracy": 0.8215604798738346,
|
| 69 |
+
"eval_num_tokens": 137472.0,
|
| 70 |
+
"eval_runtime": 86.8692,
|
| 71 |
+
"eval_samples_per_second": 15.84,
|
| 72 |
+
"eval_steps_per_second": 1.98,
|
| 73 |
+
"step": 60
|
| 74 |
+
},
|
| 75 |
+
{
|
| 76 |
+
"entropy": 0.7071127541363239,
|
| 77 |
+
"epoch": 0.199252801992528,
|
| 78 |
+
"grad_norm": 1.387060284614563,
|
| 79 |
+
"learning_rate": 3.960869968583232e-05,
|
| 80 |
+
"loss": 0.6382100582122803,
|
| 81 |
+
"mean_token_accuracy": 0.8229366384446621,
|
| 82 |
+
"num_tokens": 187408.0,
|
| 83 |
+
"step": 80
|
| 84 |
+
},
|
| 85 |
+
{
|
| 86 |
+
"epoch": 0.199252801992528,
|
| 87 |
+
"eval_entropy": 0.6883931482254073,
|
| 88 |
+
"eval_loss": 0.625065803527832,
|
| 89 |
+
"eval_mean_token_accuracy": 0.828940509710201,
|
| 90 |
+
"eval_num_tokens": 187408.0,
|
| 91 |
+
"eval_runtime": 86.662,
|
| 92 |
+
"eval_samples_per_second": 15.878,
|
| 93 |
+
"eval_steps_per_second": 1.985,
|
| 94 |
+
"step": 80
|
| 95 |
+
},
|
| 96 |
+
{
|
| 97 |
+
"entropy": 0.6800824083387852,
|
| 98 |
+
"epoch": 0.24906600249066002,
|
| 99 |
+
"grad_norm": 0.9892916679382324,
|
| 100 |
+
"learning_rate": 4.963621859363797e-05,
|
| 101 |
+
"loss": 0.6011715888977051,
|
| 102 |
+
"mean_token_accuracy": 0.8323964163661003,
|
| 103 |
+
"num_tokens": 234197.0,
|
| 104 |
+
"step": 100
|
| 105 |
+
},
|
| 106 |
+
{
|
| 107 |
+
"epoch": 0.24906600249066002,
|
| 108 |
+
"eval_entropy": 0.6840810470802839,
|
| 109 |
+
"eval_loss": 0.6037028431892395,
|
| 110 |
+
"eval_mean_token_accuracy": 0.8309669033732525,
|
| 111 |
+
"eval_num_tokens": 234197.0,
|
| 112 |
+
"eval_runtime": 86.4637,
|
| 113 |
+
"eval_samples_per_second": 15.914,
|
| 114 |
+
"eval_steps_per_second": 1.989,
|
| 115 |
+
"step": 100
|
| 116 |
+
},
|
| 117 |
+
{
|
| 118 |
+
"entropy": 0.6776216626167297,
|
| 119 |
+
"epoch": 0.298879202988792,
|
| 120 |
+
"grad_norm": 0.8918434977531433,
|
| 121 |
+
"learning_rate": 5.9663737501443624e-05,
|
| 122 |
+
"loss": 0.5991742610931396,
|
| 123 |
+
"mean_token_accuracy": 0.8300838828086853,
|
| 124 |
+
"num_tokens": 281241.0,
|
| 125 |
+
"step": 120
|
| 126 |
+
},
|
| 127 |
+
{
|
| 128 |
+
"epoch": 0.298879202988792,
|
| 129 |
+
"eval_entropy": 0.690427724705186,
|
| 130 |
+
"eval_loss": 0.5939701795578003,
|
| 131 |
+
"eval_mean_token_accuracy": 0.8345950186945671,
|
| 132 |
+
"eval_num_tokens": 281241.0,
|
| 133 |
+
"eval_runtime": 86.6626,
|
| 134 |
+
"eval_samples_per_second": 15.878,
|
| 135 |
+
"eval_steps_per_second": 1.985,
|
| 136 |
+
"step": 120
|
| 137 |
+
},
|
| 138 |
+
{
|
| 139 |
+
"entropy": 0.6709842771291733,
|
| 140 |
+
"epoch": 0.34869240348692404,
|
| 141 |
+
"grad_norm": 0.9135531187057495,
|
| 142 |
+
"learning_rate": 6.969125640924927e-05,
|
| 143 |
+
"loss": 0.5914147377014161,
|
| 144 |
+
"mean_token_accuracy": 0.8314545609056949,
|
| 145 |
+
"num_tokens": 327393.0,
|
| 146 |
+
"step": 140
|
| 147 |
+
},
|
| 148 |
+
{
|
| 149 |
+
"epoch": 0.34869240348692404,
|
| 150 |
+
"eval_entropy": 0.6584504666023476,
|
| 151 |
+
"eval_loss": 0.5849721431732178,
|
| 152 |
+
"eval_mean_token_accuracy": 0.8357757236375365,
|
| 153 |
+
"eval_num_tokens": 327393.0,
|
| 154 |
+
"eval_runtime": 86.3262,
|
| 155 |
+
"eval_samples_per_second": 15.94,
|
| 156 |
+
"eval_steps_per_second": 1.992,
|
| 157 |
+
"step": 140
|
| 158 |
+
},
|
| 159 |
+
{
|
| 160 |
+
"entropy": 0.6524647936224938,
|
| 161 |
+
"epoch": 0.398505603985056,
|
| 162 |
+
"grad_norm": 0.8651587963104248,
|
| 163 |
+
"learning_rate": 7.971877531705493e-05,
|
| 164 |
+
"loss": 0.5710843563079834,
|
| 165 |
+
"mean_token_accuracy": 0.8396127380430698,
|
| 166 |
+
"num_tokens": 373834.0,
|
| 167 |
+
"step": 160
|
| 168 |
+
},
|
| 169 |
+
{
|
| 170 |
+
"epoch": 0.398505603985056,
|
| 171 |
+
"eval_entropy": 0.6283470298661742,
|
| 172 |
+
"eval_loss": 0.5738973617553711,
|
| 173 |
+
"eval_mean_token_accuracy": 0.8379981181649274,
|
| 174 |
+
"eval_num_tokens": 373834.0,
|
| 175 |
+
"eval_runtime": 86.5619,
|
| 176 |
+
"eval_samples_per_second": 15.896,
|
| 177 |
+
"eval_steps_per_second": 1.987,
|
| 178 |
+
"step": 160
|
| 179 |
+
},
|
| 180 |
+
{
|
| 181 |
+
"entropy": 0.6450445972383022,
|
| 182 |
+
"epoch": 0.44831880448318806,
|
| 183 |
+
"grad_norm": 0.8661723732948303,
|
| 184 |
+
"learning_rate": 8.974629422486058e-05,
|
| 185 |
+
"loss": 0.5677794933319091,
|
| 186 |
+
"mean_token_accuracy": 0.8389350369572639,
|
| 187 |
+
"num_tokens": 422572.0,
|
| 188 |
+
"step": 180
|
| 189 |
+
},
|
| 190 |
+
{
|
| 191 |
+
"epoch": 0.44831880448318806,
|
| 192 |
+
"eval_entropy": 0.6142613257086554,
|
| 193 |
+
"eval_loss": 0.5698265433311462,
|
| 194 |
+
"eval_mean_token_accuracy": 0.8388577273418737,
|
| 195 |
+
"eval_num_tokens": 422572.0,
|
| 196 |
+
"eval_runtime": 86.4443,
|
| 197 |
+
"eval_samples_per_second": 15.918,
|
| 198 |
+
"eval_steps_per_second": 1.99,
|
| 199 |
+
"step": 180
|
| 200 |
+
},
|
| 201 |
+
{
|
| 202 |
+
"entropy": 0.6448334597051144,
|
| 203 |
+
"epoch": 0.49813200498132004,
|
| 204 |
+
"grad_norm": 0.9662242531776428,
|
| 205 |
+
"learning_rate": 9.977381313266624e-05,
|
| 206 |
+
"loss": 0.581433916091919,
|
| 207 |
+
"mean_token_accuracy": 0.8387043006718159,
|
| 208 |
+
"num_tokens": 471879.0,
|
| 209 |
+
"step": 200
|
| 210 |
+
},
|
| 211 |
+
{
|
| 212 |
+
"epoch": 0.49813200498132004,
|
| 213 |
+
"eval_entropy": 0.6154296522916749,
|
| 214 |
+
"eval_loss": 0.5660303831100464,
|
| 215 |
+
"eval_mean_token_accuracy": 0.8412494766850804,
|
| 216 |
+
"eval_num_tokens": 471879.0,
|
| 217 |
+
"eval_runtime": 86.3063,
|
| 218 |
+
"eval_samples_per_second": 15.943,
|
| 219 |
+
"eval_steps_per_second": 1.993,
|
| 220 |
+
"step": 200
|
| 221 |
+
},
|
| 222 |
+
{
|
| 223 |
+
"entropy": 0.6376728117465973,
|
| 224 |
+
"epoch": 0.547945205479452,
|
| 225 |
+
"grad_norm": 0.7618638873100281,
|
| 226 |
+
"learning_rate": 0.00010980133204047189,
|
| 227 |
+
"loss": 0.5678351402282715,
|
| 228 |
+
"mean_token_accuracy": 0.8404546812176704,
|
| 229 |
+
"num_tokens": 520984.0,
|
| 230 |
+
"step": 220
|
| 231 |
+
},
|
| 232 |
+
{
|
| 233 |
+
"epoch": 0.547945205479452,
|
| 234 |
+
"eval_entropy": 0.6181817033956217,
|
| 235 |
+
"eval_loss": 0.5663750171661377,
|
| 236 |
+
"eval_mean_token_accuracy": 0.8388350962899452,
|
| 237 |
+
"eval_num_tokens": 520984.0,
|
| 238 |
+
"eval_runtime": 86.5904,
|
| 239 |
+
"eval_samples_per_second": 15.891,
|
| 240 |
+
"eval_steps_per_second": 1.986,
|
| 241 |
+
"step": 220
|
| 242 |
+
},
|
| 243 |
+
{
|
| 244 |
+
"entropy": 0.6303176879882812,
|
| 245 |
+
"epoch": 0.597758405977584,
|
| 246 |
+
"grad_norm": 0.7571695446968079,
|
| 247 |
+
"learning_rate": 0.00011982885094827753,
|
| 248 |
+
"loss": 0.5502778053283691,
|
| 249 |
+
"mean_token_accuracy": 0.8429657347500324,
|
| 250 |
+
"num_tokens": 566596.0,
|
| 251 |
+
"step": 240
|
| 252 |
+
},
|
| 253 |
+
{
|
| 254 |
+
"epoch": 0.597758405977584,
|
| 255 |
+
"eval_entropy": 0.6252533817707107,
|
| 256 |
+
"eval_loss": 0.5570284128189087,
|
| 257 |
+
"eval_mean_token_accuracy": 0.8427327847064927,
|
| 258 |
+
"eval_num_tokens": 566596.0,
|
| 259 |
+
"eval_runtime": 86.4157,
|
| 260 |
+
"eval_samples_per_second": 15.923,
|
| 261 |
+
"eval_steps_per_second": 1.99,
|
| 262 |
+
"step": 240
|
| 263 |
+
},
|
| 264 |
+
{
|
| 265 |
+
"entropy": 0.6202544964849949,
|
| 266 |
+
"epoch": 0.6475716064757161,
|
| 267 |
+
"grad_norm": 0.6447190642356873,
|
| 268 |
+
"learning_rate": 0.00012985636985608318,
|
| 269 |
+
"loss": 0.5485352993011474,
|
| 270 |
+
"mean_token_accuracy": 0.844165726006031,
|
| 271 |
+
"num_tokens": 613603.0,
|
| 272 |
+
"step": 260
|
| 273 |
+
},
|
| 274 |
+
{
|
| 275 |
+
"epoch": 0.6475716064757161,
|
| 276 |
+
"eval_entropy": 0.6441633552312851,
|
| 277 |
+
"eval_loss": 0.5606644153594971,
|
| 278 |
+
"eval_mean_token_accuracy": 0.842403513054515,
|
| 279 |
+
"eval_num_tokens": 613603.0,
|
| 280 |
+
"eval_runtime": 86.6343,
|
| 281 |
+
"eval_samples_per_second": 15.883,
|
| 282 |
+
"eval_steps_per_second": 1.985,
|
| 283 |
+
"step": 260
|
| 284 |
+
},
|
| 285 |
+
{
|
| 286 |
+
"entropy": 0.6306711677461863,
|
| 287 |
+
"epoch": 0.6973848069738481,
|
| 288 |
+
"grad_norm": 0.7869907021522522,
|
| 289 |
+
"learning_rate": 0.00013988388876388883,
|
| 290 |
+
"loss": 0.5579307556152344,
|
| 291 |
+
"mean_token_accuracy": 0.841247134655714,
|
| 292 |
+
"num_tokens": 658565.0,
|
| 293 |
+
"step": 280
|
| 294 |
+
},
|
| 295 |
+
{
|
| 296 |
+
"epoch": 0.6973848069738481,
|
| 297 |
+
"eval_entropy": 0.6263934678809587,
|
| 298 |
+
"eval_loss": 0.5559113025665283,
|
| 299 |
+
"eval_mean_token_accuracy": 0.8427334743183713,
|
| 300 |
+
"eval_num_tokens": 658565.0,
|
| 301 |
+
"eval_runtime": 86.6403,
|
| 302 |
+
"eval_samples_per_second": 15.882,
|
| 303 |
+
"eval_steps_per_second": 1.985,
|
| 304 |
+
"step": 280
|
| 305 |
+
},
|
| 306 |
+
{
|
| 307 |
+
"entropy": 0.6385872110724449,
|
| 308 |
+
"epoch": 0.7471980074719801,
|
| 309 |
+
"grad_norm": 0.6679229736328125,
|
| 310 |
+
"learning_rate": 0.0001499114076716945,
|
| 311 |
+
"loss": 0.5667279720306396,
|
| 312 |
+
"mean_token_accuracy": 0.8389136254787445,
|
| 313 |
+
"num_tokens": 705680.0,
|
| 314 |
+
"step": 300
|
| 315 |
+
},
|
| 316 |
+
{
|
| 317 |
+
"epoch": 0.7471980074719801,
|
| 318 |
+
"eval_entropy": 0.6141417321077612,
|
| 319 |
+
"eval_loss": 0.5570600628852844,
|
| 320 |
+
"eval_mean_token_accuracy": 0.8437647996253745,
|
| 321 |
+
"eval_num_tokens": 705680.0,
|
| 322 |
+
"eval_runtime": 86.7588,
|
| 323 |
+
"eval_samples_per_second": 15.86,
|
| 324 |
+
"eval_steps_per_second": 1.983,
|
| 325 |
+
"step": 300
|
| 326 |
+
},
|
| 327 |
+
{
|
| 328 |
+
"entropy": 0.6199494235217571,
|
| 329 |
+
"epoch": 0.797011207970112,
|
| 330 |
+
"grad_norm": 0.7924400568008423,
|
| 331 |
+
"learning_rate": 0.00015993892657950015,
|
| 332 |
+
"loss": 0.5529299736022949,
|
| 333 |
+
"mean_token_accuracy": 0.8426973208785057,
|
| 334 |
+
"num_tokens": 752616.0,
|
| 335 |
+
"step": 320
|
| 336 |
+
},
|
| 337 |
+
{
|
| 338 |
+
"epoch": 0.797011207970112,
|
| 339 |
+
"eval_entropy": 0.6133768925833147,
|
| 340 |
+
"eval_loss": 0.556602418422699,
|
| 341 |
+
"eval_mean_token_accuracy": 0.8432947965555413,
|
| 342 |
+
"eval_num_tokens": 752616.0,
|
| 343 |
+
"eval_runtime": 86.492,
|
| 344 |
+
"eval_samples_per_second": 15.909,
|
| 345 |
+
"eval_steps_per_second": 1.989,
|
| 346 |
+
"step": 320
|
| 347 |
+
},
|
| 348 |
+
{
|
| 349 |
+
"entropy": 0.6203986253589392,
|
| 350 |
+
"epoch": 0.8468244084682441,
|
| 351 |
+
"grad_norm": 0.8364354372024536,
|
| 352 |
+
"learning_rate": 0.00016996644548730578,
|
| 353 |
+
"loss": 0.5551144123077393,
|
| 354 |
+
"mean_token_accuracy": 0.8432973213493824,
|
| 355 |
+
"num_tokens": 797151.0,
|
| 356 |
+
"step": 340
|
| 357 |
+
},
|
| 358 |
+
{
|
| 359 |
+
"epoch": 0.8468244084682441,
|
| 360 |
+
"eval_entropy": 0.6017442844634833,
|
| 361 |
+
"eval_loss": 0.5566568374633789,
|
| 362 |
+
"eval_mean_token_accuracy": 0.8437666123689607,
|
| 363 |
+
"eval_num_tokens": 797151.0,
|
| 364 |
+
"eval_runtime": 86.5552,
|
| 365 |
+
"eval_samples_per_second": 15.897,
|
| 366 |
+
"eval_steps_per_second": 1.987,
|
| 367 |
+
"step": 340
|
| 368 |
+
},
|
| 369 |
+
{
|
| 370 |
+
"entropy": 0.6341533534228802,
|
| 371 |
+
"epoch": 0.8966376089663761,
|
| 372 |
+
"grad_norm": 0.7783445715904236,
|
| 373 |
+
"learning_rate": 0.00017999396439511144,
|
| 374 |
+
"loss": 0.5669133186340332,
|
| 375 |
+
"mean_token_accuracy": 0.8379446342587471,
|
| 376 |
+
"num_tokens": 843585.0,
|
| 377 |
+
"step": 360
|
| 378 |
+
},
|
| 379 |
+
{
|
| 380 |
+
"epoch": 0.8966376089663761,
|
| 381 |
+
"eval_entropy": 0.6055107958788095,
|
| 382 |
+
"eval_loss": 0.5599350333213806,
|
| 383 |
+
"eval_mean_token_accuracy": 0.8435030894917112,
|
| 384 |
+
"eval_num_tokens": 843585.0,
|
| 385 |
+
"eval_runtime": 86.4814,
|
| 386 |
+
"eval_samples_per_second": 15.911,
|
| 387 |
+
"eval_steps_per_second": 1.989,
|
| 388 |
+
"step": 360
|
| 389 |
+
},
|
| 390 |
+
{
|
| 391 |
+
"entropy": 0.6306198488920927,
|
| 392 |
+
"epoch": 0.9464508094645081,
|
| 393 |
+
"grad_norm": 0.8449786901473999,
|
| 394 |
+
"learning_rate": 0.0001900214833029171,
|
| 395 |
+
"loss": 0.5739435195922852,
|
| 396 |
+
"mean_token_accuracy": 0.8393832489848136,
|
| 397 |
+
"num_tokens": 889842.0,
|
| 398 |
+
"step": 380
|
| 399 |
+
},
|
| 400 |
+
{
|
| 401 |
+
"epoch": 0.9464508094645081,
|
| 402 |
+
"eval_entropy": 0.6129532439071078,
|
| 403 |
+
"eval_loss": 0.5566295981407166,
|
| 404 |
+
"eval_mean_token_accuracy": 0.8430350880290187,
|
| 405 |
+
"eval_num_tokens": 889842.0,
|
| 406 |
+
"eval_runtime": 86.4643,
|
| 407 |
+
"eval_samples_per_second": 15.914,
|
| 408 |
+
"eval_steps_per_second": 1.989,
|
| 409 |
+
"step": 380
|
| 410 |
+
},
|
| 411 |
+
{
|
| 412 |
+
"entropy": 0.6203123550862074,
|
| 413 |
+
"epoch": 0.9962640099626401,
|
| 414 |
+
"grad_norm": 0.7334314584732056,
|
| 415 |
+
"learning_rate": 0.00020004900221072276,
|
| 416 |
+
"loss": 0.5547565937042236,
|
| 417 |
+
"mean_token_accuracy": 0.8403573960065842,
|
| 418 |
+
"num_tokens": 935589.0,
|
| 419 |
+
"step": 400
|
| 420 |
+
},
|
| 421 |
+
{
|
| 422 |
+
"epoch": 0.9962640099626401,
|
| 423 |
+
"eval_entropy": 0.6275761647279873,
|
| 424 |
+
"eval_loss": 0.5621116757392883,
|
| 425 |
+
"eval_mean_token_accuracy": 0.841587379228237,
|
| 426 |
+
"eval_num_tokens": 935589.0,
|
| 427 |
+
"eval_runtime": 86.4748,
|
| 428 |
+
"eval_samples_per_second": 15.912,
|
| 429 |
+
"eval_steps_per_second": 1.989,
|
| 430 |
+
"step": 400
|
| 431 |
+
},
|
| 432 |
+
{
|
| 433 |
+
"entropy": 0.5795013002860241,
|
| 434 |
+
"epoch": 1.0448318804483188,
|
| 435 |
+
"grad_norm": 0.8858296871185303,
|
| 436 |
+
"learning_rate": 0.0002015421505577756,
|
| 437 |
+
"loss": 0.5183939933776855,
|
| 438 |
+
"mean_token_accuracy": 0.850081592034071,
|
| 439 |
+
"num_tokens": 980589.0,
|
| 440 |
+
"step": 420
|
| 441 |
+
},
|
| 442 |
+
{
|
| 443 |
+
"epoch": 1.0448318804483188,
|
| 444 |
+
"eval_entropy": 0.5583065545489622,
|
| 445 |
+
"eval_loss": 0.5605642199516296,
|
| 446 |
+
"eval_mean_token_accuracy": 0.8439708411000496,
|
| 447 |
+
"eval_num_tokens": 980589.0,
|
| 448 |
+
"eval_runtime": 86.5422,
|
| 449 |
+
"eval_samples_per_second": 15.9,
|
| 450 |
+
"eval_steps_per_second": 1.987,
|
| 451 |
+
"step": 420
|
| 452 |
+
},
|
| 453 |
+
{
|
| 454 |
+
"entropy": 0.5671238023787737,
|
| 455 |
+
"epoch": 1.0946450809464507,
|
| 456 |
+
"grad_norm": 0.6882498264312744,
|
| 457 |
+
"learning_rate": 0.00020150112347025443,
|
| 458 |
+
"loss": 0.5077326774597168,
|
| 459 |
+
"mean_token_accuracy": 0.8489868573844432,
|
| 460 |
+
"num_tokens": 1027852.0,
|
| 461 |
+
"step": 440
|
| 462 |
+
},
|
| 463 |
+
{
|
| 464 |
+
"epoch": 1.0946450809464507,
|
| 465 |
+
"eval_entropy": 0.5868900277933409,
|
| 466 |
+
"eval_loss": 0.5602695345878601,
|
| 467 |
+
"eval_mean_token_accuracy": 0.8428842161977014,
|
| 468 |
+
"eval_num_tokens": 1027852.0,
|
| 469 |
+
"eval_runtime": 86.623,
|
| 470 |
+
"eval_samples_per_second": 15.885,
|
| 471 |
+
"eval_steps_per_second": 1.986,
|
| 472 |
+
"step": 440
|
| 473 |
+
},
|
| 474 |
+
{
|
| 475 |
+
"entropy": 0.5533561781048775,
|
| 476 |
+
"epoch": 1.1444582814445827,
|
| 477 |
+
"grad_norm": 0.7717723250389099,
|
| 478 |
+
"learning_rate": 0.0002014297192297181,
|
| 479 |
+
"loss": 0.4954517364501953,
|
| 480 |
+
"mean_token_accuracy": 0.8529035650193691,
|
| 481 |
+
"num_tokens": 1077649.0,
|
| 482 |
+
"step": 460
|
| 483 |
+
},
|
| 484 |
+
{
|
| 485 |
+
"epoch": 1.1444582814445827,
|
| 486 |
+
"eval_entropy": 0.5600803743961246,
|
| 487 |
+
"eval_loss": 0.5608077645301819,
|
| 488 |
+
"eval_mean_token_accuracy": 0.8445036771685578,
|
| 489 |
+
"eval_num_tokens": 1077649.0,
|
| 490 |
+
"eval_runtime": 86.1316,
|
| 491 |
+
"eval_samples_per_second": 15.976,
|
| 492 |
+
"eval_steps_per_second": 1.997,
|
| 493 |
+
"step": 460
|
| 494 |
+
},
|
| 495 |
+
{
|
| 496 |
+
"entropy": 0.5692154694348573,
|
| 497 |
+
"epoch": 1.1942714819427147,
|
| 498 |
+
"grad_norm": 0.7322827577590942,
|
| 499 |
+
"learning_rate": 0.0002013279593707117,
|
| 500 |
+
"loss": 0.505049467086792,
|
| 501 |
+
"mean_token_accuracy": 0.8551576808094978,
|
| 502 |
+
"num_tokens": 1124872.0,
|
| 503 |
+
"step": 480
|
| 504 |
+
},
|
| 505 |
+
{
|
| 506 |
+
"epoch": 1.1942714819427147,
|
| 507 |
+
"eval_entropy": 0.5732695829383162,
|
| 508 |
+
"eval_loss": 0.5594323873519897,
|
| 509 |
+
"eval_mean_token_accuracy": 0.8449713407560836,
|
| 510 |
+
"eval_num_tokens": 1124872.0,
|
| 511 |
+
"eval_runtime": 86.2726,
|
| 512 |
+
"eval_samples_per_second": 15.949,
|
| 513 |
+
"eval_steps_per_second": 1.994,
|
| 514 |
+
"step": 480
|
| 515 |
+
},
|
| 516 |
+
{
|
| 517 |
+
"entropy": 0.5817618492990733,
|
| 518 |
+
"epoch": 1.244084682440847,
|
| 519 |
+
"grad_norm": 1.1776764392852783,
|
| 520 |
+
"learning_rate": 0.0002011958745826208,
|
| 521 |
+
"loss": 0.5137609958648681,
|
| 522 |
+
"mean_token_accuracy": 0.8521522544324398,
|
| 523 |
+
"num_tokens": 1168698.0,
|
| 524 |
+
"step": 500
|
| 525 |
+
},
|
| 526 |
+
{
|
| 527 |
+
"epoch": 1.244084682440847,
|
| 528 |
+
"eval_entropy": 0.5662581343636957,
|
| 529 |
+
"eval_loss": 0.5595026016235352,
|
| 530 |
+
"eval_mean_token_accuracy": 0.8441977164773053,
|
| 531 |
+
"eval_num_tokens": 1168698.0,
|
| 532 |
+
"eval_runtime": 86.7261,
|
| 533 |
+
"eval_samples_per_second": 15.866,
|
| 534 |
+
"eval_steps_per_second": 1.983,
|
| 535 |
+
"step": 500
|
| 536 |
+
},
|
| 537 |
+
{
|
| 538 |
+
"entropy": 0.5712925456464291,
|
| 539 |
+
"epoch": 1.293897882938979,
|
| 540 |
+
"grad_norm": 0.7960361838340759,
|
| 541 |
+
"learning_rate": 0.0002010335047004159,
|
| 542 |
+
"loss": 0.5134767532348633,
|
| 543 |
+
"mean_token_accuracy": 0.8513577707111836,
|
| 544 |
+
"num_tokens": 1216679.0,
|
| 545 |
+
"step": 520
|
| 546 |
+
},
|
| 547 |
+
{
|
| 548 |
+
"epoch": 1.293897882938979,
|
| 549 |
+
"eval_entropy": 0.5441222797299541,
|
| 550 |
+
"eval_loss": 0.5535460114479065,
|
| 551 |
+
"eval_mean_token_accuracy": 0.8450886118550633,
|
| 552 |
+
"eval_num_tokens": 1216679.0,
|
| 553 |
+
"eval_runtime": 86.2675,
|
| 554 |
+
"eval_samples_per_second": 15.95,
|
| 555 |
+
"eval_steps_per_second": 1.994,
|
| 556 |
+
"step": 520
|
| 557 |
+
},
|
| 558 |
+
{
|
| 559 |
+
"entropy": 0.5787045754492283,
|
| 560 |
+
"epoch": 1.3437110834371109,
|
| 561 |
+
"grad_norm": 0.9205410480499268,
|
| 562 |
+
"learning_rate": 0.00020084089869263887,
|
| 563 |
+
"loss": 0.5119701862335205,
|
| 564 |
+
"mean_token_accuracy": 0.8503516331315041,
|
| 565 |
+
"num_tokens": 1261365.0,
|
| 566 |
+
"step": 540
|
| 567 |
+
},
|
| 568 |
+
{
|
| 569 |
+
"epoch": 1.3437110834371109,
|
| 570 |
+
"eval_entropy": 0.5744457827057949,
|
| 571 |
+
"eval_loss": 0.5514978766441345,
|
| 572 |
+
"eval_mean_token_accuracy": 0.845929987901865,
|
| 573 |
+
"eval_num_tokens": 1261365.0,
|
| 574 |
+
"eval_runtime": 86.2299,
|
| 575 |
+
"eval_samples_per_second": 15.957,
|
| 576 |
+
"eval_steps_per_second": 1.995,
|
| 577 |
+
"step": 540
|
| 578 |
+
},
|
| 579 |
+
{
|
| 580 |
+
"entropy": 0.5739392962306737,
|
| 581 |
+
"epoch": 1.3935242839352429,
|
| 582 |
+
"grad_norm": 0.7475653886795044,
|
| 583 |
+
"learning_rate": 0.00020061811464663464,
|
| 584 |
+
"loss": 0.5189042091369629,
|
| 585 |
+
"mean_token_accuracy": 0.8492388024926185,
|
| 586 |
+
"num_tokens": 1306879.0,
|
| 587 |
+
"step": 560
|
| 588 |
+
},
|
| 589 |
+
{
|
| 590 |
+
"epoch": 1.3935242839352429,
|
| 591 |
+
"eval_entropy": 0.6116398271433142,
|
| 592 |
+
"eval_loss": 0.551732063293457,
|
| 593 |
+
"eval_mean_token_accuracy": 0.8450756967067719,
|
| 594 |
+
"eval_num_tokens": 1306879.0,
|
| 595 |
+
"eval_runtime": 86.6081,
|
| 596 |
+
"eval_samples_per_second": 15.888,
|
| 597 |
+
"eval_steps_per_second": 1.986,
|
| 598 |
+
"step": 560
|
| 599 |
+
},
|
| 600 |
+
{
|
| 601 |
+
"entropy": 0.5755622573196888,
|
| 602 |
+
"epoch": 1.4433374844333748,
|
| 603 |
+
"grad_norm": 0.8218411803245544,
|
| 604 |
+
"learning_rate": 0.00020036521975103286,
|
| 605 |
+
"loss": 0.5106248378753662,
|
| 606 |
+
"mean_token_accuracy": 0.8506785586476326,
|
| 607 |
+
"num_tokens": 1353534.0,
|
| 608 |
+
"step": 580
|
| 609 |
+
},
|
| 610 |
+
{
|
| 611 |
+
"epoch": 1.4433374844333748,
|
| 612 |
+
"eval_entropy": 0.5906928708386976,
|
| 613 |
+
"eval_loss": 0.551278829574585,
|
| 614 |
+
"eval_mean_token_accuracy": 0.8462819308042526,
|
| 615 |
+
"eval_num_tokens": 1353534.0,
|
| 616 |
+
"eval_runtime": 86.5438,
|
| 617 |
+
"eval_samples_per_second": 15.899,
|
| 618 |
+
"eval_steps_per_second": 1.987,
|
| 619 |
+
"step": 580
|
| 620 |
+
},
|
| 621 |
+
{
|
| 622 |
+
"entropy": 0.5694822132587433,
|
| 623 |
+
"epoch": 1.4931506849315068,
|
| 624 |
+
"grad_norm": 0.8880652189254761,
|
| 625 |
+
"learning_rate": 0.00020008229027548475,
|
| 626 |
+
"loss": 0.5140334606170655,
|
| 627 |
+
"mean_token_accuracy": 0.8521522797644139,
|
| 628 |
+
"num_tokens": 1399537.0,
|
| 629 |
+
"step": 600
|
| 630 |
+
},
|
| 631 |
+
{
|
| 632 |
+
"epoch": 1.4931506849315068,
|
| 633 |
+
"eval_entropy": 0.5599641964532608,
|
| 634 |
+
"eval_loss": 0.5501875877380371,
|
| 635 |
+
"eval_mean_token_accuracy": 0.8467660788879838,
|
| 636 |
+
"eval_num_tokens": 1399537.0,
|
| 637 |
+
"eval_runtime": 86.6458,
|
| 638 |
+
"eval_samples_per_second": 15.881,
|
| 639 |
+
"eval_steps_per_second": 1.985,
|
| 640 |
+
"step": 600
|
| 641 |
+
},
|
| 642 |
+
{
|
| 643 |
+
"entropy": 0.5675108034163714,
|
| 644 |
+
"epoch": 1.5429638854296388,
|
| 645 |
+
"grad_norm": 0.837087094783783,
|
| 646 |
+
"learning_rate": 0.0001997694115476612,
|
| 647 |
+
"loss": 0.5099846363067627,
|
| 648 |
+
"mean_token_accuracy": 0.8543680295348167,
|
| 649 |
+
"num_tokens": 1448422.0,
|
| 650 |
+
"step": 620
|
| 651 |
+
},
|
| 652 |
+
{
|
| 653 |
+
"epoch": 1.5429638854296388,
|
| 654 |
+
"eval_entropy": 0.5728072581249614,
|
| 655 |
+
"eval_loss": 0.5445425510406494,
|
| 656 |
+
"eval_mean_token_accuracy": 0.8474342175001321,
|
| 657 |
+
"eval_num_tokens": 1448422.0,
|
| 658 |
+
"eval_runtime": 86.4859,
|
| 659 |
+
"eval_samples_per_second": 15.91,
|
| 660 |
+
"eval_steps_per_second": 1.989,
|
| 661 |
+
"step": 620
|
| 662 |
+
},
|
| 663 |
+
{
|
| 664 |
+
"entropy": 0.5700885068625212,
|
| 665 |
+
"epoch": 1.592777085927771,
|
| 666 |
+
"grad_norm": 0.6598765850067139,
|
| 667 |
+
"learning_rate": 0.000199426677927519,
|
| 668 |
+
"loss": 0.5122694969177246,
|
| 669 |
+
"mean_token_accuracy": 0.8519927568733692,
|
| 670 |
+
"num_tokens": 1495009.0,
|
| 671 |
+
"step": 640
|
| 672 |
+
},
|
| 673 |
+
{
|
| 674 |
+
"epoch": 1.592777085927771,
|
| 675 |
+
"eval_entropy": 0.5476993622128353,
|
| 676 |
+
"eval_loss": 0.5427973866462708,
|
| 677 |
+
"eval_mean_token_accuracy": 0.8478512147138285,
|
| 678 |
+
"eval_num_tokens": 1495009.0,
|
| 679 |
+
"eval_runtime": 86.4172,
|
| 680 |
+
"eval_samples_per_second": 15.923,
|
| 681 |
+
"eval_steps_per_second": 1.99,
|
| 682 |
+
"step": 640
|
| 683 |
+
},
|
| 684 |
+
{
|
| 685 |
+
"entropy": 0.5829229176044464,
|
| 686 |
+
"epoch": 1.6425902864259028,
|
| 687 |
+
"grad_norm": 0.6965194940567017,
|
| 688 |
+
"learning_rate": 0.00019905419277884342,
|
| 689 |
+
"loss": 0.5253659725189209,
|
| 690 |
+
"mean_token_accuracy": 0.8493309423327446,
|
| 691 |
+
"num_tokens": 1536932.0,
|
| 692 |
+
"step": 660
|
| 693 |
+
},
|
| 694 |
+
{
|
| 695 |
+
"epoch": 1.6425902864259028,
|
| 696 |
+
"eval_entropy": 0.5666290084983028,
|
| 697 |
+
"eval_loss": 0.5467478036880493,
|
| 698 |
+
"eval_mean_token_accuracy": 0.8479407703460649,
|
| 699 |
+
"eval_num_tokens": 1536932.0,
|
| 700 |
+
"eval_runtime": 86.4414,
|
| 701 |
+
"eval_samples_per_second": 15.918,
|
| 702 |
+
"eval_steps_per_second": 1.99,
|
| 703 |
+
"step": 660
|
| 704 |
+
},
|
| 705 |
+
{
|
| 706 |
+
"entropy": 0.5498311135917902,
|
| 707 |
+
"epoch": 1.692403486924035,
|
| 708 |
+
"grad_norm": 0.636583685874939,
|
| 709 |
+
"learning_rate": 0.00019865206843807482,
|
| 710 |
+
"loss": 0.49981012344360354,
|
| 711 |
+
"mean_token_accuracy": 0.8560848504304885,
|
| 712 |
+
"num_tokens": 1585718.0,
|
| 713 |
+
"step": 680
|
| 714 |
+
},
|
| 715 |
+
{
|
| 716 |
+
"epoch": 1.692403486924035,
|
| 717 |
+
"eval_entropy": 0.539117265406043,
|
| 718 |
+
"eval_loss": 0.53994220495224,
|
| 719 |
+
"eval_mean_token_accuracy": 0.8488582601380903,
|
| 720 |
+
"eval_num_tokens": 1585718.0,
|
| 721 |
+
"eval_runtime": 86.5296,
|
| 722 |
+
"eval_samples_per_second": 15.902,
|
| 723 |
+
"eval_steps_per_second": 1.988,
|
| 724 |
+
"step": 680
|
| 725 |
+
},
|
| 726 |
+
{
|
| 727 |
+
"entropy": 0.5543891470879316,
|
| 728 |
+
"epoch": 1.7422166874221667,
|
| 729 |
+
"grad_norm": 0.6068442463874817,
|
| 730 |
+
"learning_rate": 0.0001982204261804297,
|
| 731 |
+
"loss": 0.498047399520874,
|
| 732 |
+
"mean_token_accuracy": 0.8554679051041603,
|
| 733 |
+
"num_tokens": 1635718.0,
|
| 734 |
+
"step": 700
|
| 735 |
+
},
|
| 736 |
+
{
|
| 737 |
+
"epoch": 1.7422166874221667,
|
| 738 |
+
"eval_entropy": 0.5703774151760478,
|
| 739 |
+
"eval_loss": 0.5300245881080627,
|
| 740 |
+
"eval_mean_token_accuracy": 0.850798153946566,
|
| 741 |
+
"eval_num_tokens": 1635718.0,
|
| 742 |
+
"eval_runtime": 86.6456,
|
| 743 |
+
"eval_samples_per_second": 15.881,
|
| 744 |
+
"eval_steps_per_second": 1.985,
|
| 745 |
+
"step": 700
|
| 746 |
+
},
|
| 747 |
+
{
|
| 748 |
+
"entropy": 0.546524541825056,
|
| 749 |
+
"epoch": 1.792029887920299,
|
| 750 |
+
"grad_norm": 0.7274155020713806,
|
| 751 |
+
"learning_rate": 0.00019775939618332566,
|
| 752 |
+
"loss": 0.4988589286804199,
|
| 753 |
+
"mean_token_accuracy": 0.853422473371029,
|
| 754 |
+
"num_tokens": 1681291.0,
|
| 755 |
+
"step": 720
|
| 756 |
+
},
|
| 757 |
+
{
|
| 758 |
+
"epoch": 1.792029887920299,
|
| 759 |
+
"eval_entropy": 0.5614905688305234,
|
| 760 |
+
"eval_loss": 0.5350332260131836,
|
| 761 |
+
"eval_mean_token_accuracy": 0.8492204359797544,
|
| 762 |
+
"eval_num_tokens": 1681291.0,
|
| 763 |
+
"eval_runtime": 86.7581,
|
| 764 |
+
"eval_samples_per_second": 15.86,
|
| 765 |
+
"eval_steps_per_second": 1.983,
|
| 766 |
+
"step": 720
|
| 767 |
+
},
|
| 768 |
+
{
|
| 769 |
+
"entropy": 0.5519792139530182,
|
| 770 |
+
"epoch": 1.841843088418431,
|
| 771 |
+
"grad_norm": 0.663466215133667,
|
| 772 |
+
"learning_rate": 0.00019726911748712167,
|
| 773 |
+
"loss": 0.5099314212799072,
|
| 774 |
+
"mean_token_accuracy": 0.848412600159645,
|
| 775 |
+
"num_tokens": 1729102.0,
|
| 776 |
+
"step": 740
|
| 777 |
+
},
|
| 778 |
+
{
|
| 779 |
+
"epoch": 1.841843088418431,
|
| 780 |
+
"eval_entropy": 0.5583519090053647,
|
| 781 |
+
"eval_loss": 0.530483603477478,
|
| 782 |
+
"eval_mean_token_accuracy": 0.8500003374593202,
|
| 783 |
+
"eval_num_tokens": 1729102.0,
|
| 784 |
+
"eval_runtime": 86.3961,
|
| 785 |
+
"eval_samples_per_second": 15.927,
|
| 786 |
+
"eval_steps_per_second": 1.991,
|
| 787 |
+
"step": 740
|
| 788 |
+
},
|
| 789 |
+
{
|
| 790 |
+
"entropy": 0.5454779766499996,
|
| 791 |
+
"epoch": 1.891656288916563,
|
| 792 |
+
"grad_norm": 0.890394926071167,
|
| 793 |
+
"learning_rate": 0.00019674973795318548,
|
| 794 |
+
"loss": 0.4931994915008545,
|
| 795 |
+
"mean_token_accuracy": 0.8540832489728928,
|
| 796 |
+
"num_tokens": 1773578.0,
|
| 797 |
+
"step": 760
|
| 798 |
+
},
|
| 799 |
+
{
|
| 800 |
+
"epoch": 1.891656288916563,
|
| 801 |
+
"eval_entropy": 0.572755502406941,
|
| 802 |
+
"eval_loss": 0.5415747761726379,
|
| 803 |
+
"eval_mean_token_accuracy": 0.8444425803284312,
|
| 804 |
+
"eval_num_tokens": 1773578.0,
|
| 805 |
+
"eval_runtime": 86.4323,
|
| 806 |
+
"eval_samples_per_second": 15.92,
|
| 807 |
+
"eval_steps_per_second": 1.99,
|
| 808 |
+
"step": 760
|
| 809 |
+
},
|
| 810 |
+
{
|
| 811 |
+
"entropy": 0.5392089951783419,
|
| 812 |
+
"epoch": 1.9414694894146949,
|
| 813 |
+
"grad_norm": 0.632411777973175,
|
| 814 |
+
"learning_rate": 0.00019620141421930058,
|
| 815 |
+
"loss": 0.4957888603210449,
|
| 816 |
+
"mean_token_accuracy": 0.8549866065382957,
|
| 817 |
+
"num_tokens": 1821725.0,
|
| 818 |
+
"step": 780
|
| 819 |
+
},
|
| 820 |
+
{
|
| 821 |
+
"epoch": 1.9414694894146949,
|
| 822 |
+
"eval_entropy": 0.540764772961306,
|
| 823 |
+
"eval_loss": 0.5327216386795044,
|
| 824 |
+
"eval_mean_token_accuracy": 0.850631088364956,
|
| 825 |
+
"eval_num_tokens": 1821725.0,
|
| 826 |
+
"eval_runtime": 86.8097,
|
| 827 |
+
"eval_samples_per_second": 15.851,
|
| 828 |
+
"eval_steps_per_second": 1.981,
|
| 829 |
+
"step": 780
|
| 830 |
+
},
|
| 831 |
+
{
|
| 832 |
+
"entropy": 0.5674678739160299,
|
| 833 |
+
"epoch": 1.9912826899128269,
|
| 834 |
+
"grad_norm": 0.6958843469619751,
|
| 835 |
+
"learning_rate": 0.0001956243116524263,
|
| 836 |
+
"loss": 0.504389762878418,
|
| 837 |
+
"mean_token_accuracy": 0.8527948908507824,
|
| 838 |
+
"num_tokens": 1868431.0,
|
| 839 |
+
"step": 800
|
| 840 |
+
},
|
| 841 |
+
{
|
| 842 |
+
"epoch": 1.9912826899128269,
|
| 843 |
+
"eval_entropy": 0.530262403190136,
|
| 844 |
+
"eval_loss": 0.5308871865272522,
|
| 845 |
+
"eval_mean_token_accuracy": 0.8522498046242913,
|
| 846 |
+
"eval_num_tokens": 1868431.0,
|
| 847 |
+
"eval_runtime": 86.7942,
|
| 848 |
+
"eval_samples_per_second": 15.854,
|
| 849 |
+
"eval_steps_per_second": 1.982,
|
| 850 |
+
"step": 800
|
| 851 |
+
},
|
| 852 |
+
{
|
| 853 |
+
"entropy": 0.4742849511213792,
|
| 854 |
+
"epoch": 2.0398505603985058,
|
| 855 |
+
"grad_norm": 0.6941492557525635,
|
| 856 |
+
"learning_rate": 0.00019501860429882556,
|
| 857 |
+
"loss": 0.418599271774292,
|
| 858 |
+
"mean_token_accuracy": 0.8748210859604371,
|
| 859 |
+
"num_tokens": 1915280.0,
|
| 860 |
+
"step": 820
|
| 861 |
+
},
|
| 862 |
+
{
|
| 863 |
+
"epoch": 2.0398505603985058,
|
| 864 |
+
"eval_entropy": 0.504602165069691,
|
| 865 |
+
"eval_loss": 0.542878270149231,
|
| 866 |
+
"eval_mean_token_accuracy": 0.8507604484641275,
|
| 867 |
+
"eval_num_tokens": 1915280.0,
|
| 868 |
+
"eval_runtime": 86.7841,
|
| 869 |
+
"eval_samples_per_second": 15.855,
|
| 870 |
+
"eval_steps_per_second": 1.982,
|
| 871 |
+
"step": 820
|
| 872 |
+
},
|
| 873 |
+
{
|
| 874 |
+
"entropy": 0.45857742577791216,
|
| 875 |
+
"epoch": 2.0896637608966375,
|
| 876 |
+
"grad_norm": 0.5791997909545898,
|
| 877 |
+
"learning_rate": 0.00019438447483157478,
|
| 878 |
+
"loss": 0.399777889251709,
|
| 879 |
+
"mean_token_accuracy": 0.8754058346152306,
|
| 880 |
+
"num_tokens": 1965306.0,
|
| 881 |
+
"step": 840
|
| 882 |
+
},
|
| 883 |
+
{
|
| 884 |
+
"epoch": 2.0896637608966375,
|
| 885 |
+
"eval_entropy": 0.5028848362176918,
|
| 886 |
+
"eval_loss": 0.5356478095054626,
|
| 887 |
+
"eval_mean_token_accuracy": 0.8525635412959165,
|
| 888 |
+
"eval_num_tokens": 1965306.0,
|
| 889 |
+
"eval_runtime": 86.6707,
|
| 890 |
+
"eval_samples_per_second": 15.876,
|
| 891 |
+
"eval_steps_per_second": 1.985,
|
| 892 |
+
"step": 840
|
| 893 |
+
},
|
| 894 |
+
{
|
| 895 |
+
"entropy": 0.4869446292519569,
|
| 896 |
+
"epoch": 2.1394769613947697,
|
| 897 |
+
"grad_norm": 0.6483516693115234,
|
| 898 |
+
"learning_rate": 0.00019372211449547223,
|
| 899 |
+
"loss": 0.40715818405151366,
|
| 900 |
+
"mean_token_accuracy": 0.875113020837307,
|
| 901 |
+
"num_tokens": 2008562.0,
|
| 902 |
+
"step": 860
|
| 903 |
+
},
|
| 904 |
+
{
|
| 905 |
+
"epoch": 2.1394769613947697,
|
| 906 |
+
"eval_entropy": 0.4928991326759028,
|
| 907 |
+
"eval_loss": 0.5419561862945557,
|
| 908 |
+
"eval_mean_token_accuracy": 0.8516040146350861,
|
| 909 |
+
"eval_num_tokens": 2008562.0,
|
| 910 |
+
"eval_runtime": 87.0686,
|
| 911 |
+
"eval_samples_per_second": 15.804,
|
| 912 |
+
"eval_steps_per_second": 1.975,
|
| 913 |
+
"step": 860
|
| 914 |
+
},
|
| 915 |
+
{
|
| 916 |
+
"entropy": 0.45819590501487256,
|
| 917 |
+
"epoch": 2.1892901618929015,
|
| 918 |
+
"grad_norm": 0.6661920547485352,
|
| 919 |
+
"learning_rate": 0.00019303172304936108,
|
| 920 |
+
"loss": 0.39511430263519287,
|
| 921 |
+
"mean_token_accuracy": 0.8780680045485496,
|
| 922 |
+
"num_tokens": 2056474.0,
|
| 923 |
+
"step": 880
|
| 924 |
+
},
|
| 925 |
+
{
|
| 926 |
+
"epoch": 2.1892901618929015,
|
| 927 |
+
"eval_entropy": 0.48602560647698334,
|
| 928 |
+
"eval_loss": 0.5436084866523743,
|
| 929 |
+
"eval_mean_token_accuracy": 0.8500938470973525,
|
| 930 |
+
"eval_num_tokens": 2056474.0,
|
| 931 |
+
"eval_runtime": 86.6809,
|
| 932 |
+
"eval_samples_per_second": 15.874,
|
| 933 |
+
"eval_steps_per_second": 1.984,
|
| 934 |
+
"step": 880
|
| 935 |
+
},
|
| 936 |
+
{
|
| 937 |
+
"entropy": 0.4780638810247183,
|
| 938 |
+
"epoch": 2.2391033623910337,
|
| 939 |
+
"grad_norm": 0.6870484352111816,
|
| 940 |
+
"learning_rate": 0.0001923135087058851,
|
| 941 |
+
"loss": 0.4061615467071533,
|
| 942 |
+
"mean_token_accuracy": 0.8766494184732437,
|
| 943 |
+
"num_tokens": 2103543.0,
|
| 944 |
+
"step": 900
|
| 945 |
+
},
|
| 946 |
+
{
|
| 947 |
+
"epoch": 2.2391033623910337,
|
| 948 |
+
"eval_entropy": 0.48236206035281337,
|
| 949 |
+
"eval_loss": 0.5446090698242188,
|
| 950 |
+
"eval_mean_token_accuracy": 0.8507725513258646,
|
| 951 |
+
"eval_num_tokens": 2103543.0,
|
| 952 |
+
"eval_runtime": 86.7398,
|
| 953 |
+
"eval_samples_per_second": 15.864,
|
| 954 |
+
"eval_steps_per_second": 1.983,
|
| 955 |
+
"step": 900
|
| 956 |
+
},
|
| 957 |
+
{
|
| 958 |
+
"entropy": 0.463029869645834,
|
| 959 |
+
"epoch": 2.2889165628891655,
|
| 960 |
+
"grad_norm": 0.6894590854644775,
|
| 961 |
+
"learning_rate": 0.00019156768806869427,
|
| 962 |
+
"loss": 0.39602413177490237,
|
| 963 |
+
"mean_token_accuracy": 0.876420046389103,
|
| 964 |
+
"num_tokens": 2147861.0,
|
| 965 |
+
"step": 920
|
| 966 |
+
},
|
| 967 |
+
{
|
| 968 |
+
"epoch": 2.2889165628891655,
|
| 969 |
+
"eval_entropy": 0.4904779093556626,
|
| 970 |
+
"eval_loss": 0.5404934287071228,
|
| 971 |
+
"eval_mean_token_accuracy": 0.852238280828609,
|
| 972 |
+
"eval_num_tokens": 2147861.0,
|
| 973 |
+
"eval_runtime": 86.5348,
|
| 974 |
+
"eval_samples_per_second": 15.901,
|
| 975 |
+
"eval_steps_per_second": 1.988,
|
| 976 |
+
"step": 920
|
| 977 |
+
},
|
| 978 |
+
{
|
| 979 |
+
"entropy": 0.4817025110125542,
|
| 980 |
+
"epoch": 2.3387297633872977,
|
| 981 |
+
"grad_norm": 0.7756227254867554,
|
| 982 |
+
"learning_rate": 0.00019079448606712033,
|
| 983 |
+
"loss": 0.4177968502044678,
|
| 984 |
+
"mean_token_accuracy": 0.8712256088852882,
|
| 985 |
+
"num_tokens": 2190561.0,
|
| 986 |
+
"step": 940
|
| 987 |
+
},
|
| 988 |
+
{
|
| 989 |
+
"epoch": 2.3387297633872977,
|
| 990 |
+
"eval_entropy": 0.5153802815218305,
|
| 991 |
+
"eval_loss": 0.5424937605857849,
|
| 992 |
+
"eval_mean_token_accuracy": 0.8506565759348315,
|
| 993 |
+
"eval_num_tokens": 2190561.0,
|
| 994 |
+
"eval_runtime": 86.8973,
|
| 995 |
+
"eval_samples_per_second": 15.835,
|
| 996 |
+
"eval_steps_per_second": 1.979,
|
| 997 |
+
"step": 940
|
| 998 |
+
},
|
| 999 |
+
{
|
| 1000 |
+
"entropy": 0.46456389091908934,
|
| 1001 |
+
"epoch": 2.3885429638854294,
|
| 1002 |
+
"grad_norm": 1.2000319957733154,
|
| 1003 |
+
"learning_rate": 0.00018999413588834105,
|
| 1004 |
+
"loss": 0.4084665775299072,
|
| 1005 |
+
"mean_token_accuracy": 0.8750658087432385,
|
| 1006 |
+
"num_tokens": 2239412.0,
|
| 1007 |
+
"step": 960
|
| 1008 |
+
},
|
| 1009 |
+
{
|
| 1010 |
+
"epoch": 2.3885429638854294,
|
| 1011 |
+
"eval_entropy": 0.4849439303195754,
|
| 1012 |
+
"eval_loss": 0.545662522315979,
|
| 1013 |
+
"eval_mean_token_accuracy": 0.8491013112456299,
|
| 1014 |
+
"eval_num_tokens": 2239412.0,
|
| 1015 |
+
"eval_runtime": 86.9049,
|
| 1016 |
+
"eval_samples_per_second": 15.833,
|
| 1017 |
+
"eval_steps_per_second": 1.979,
|
| 1018 |
+
"step": 960
|
| 1019 |
+
},
|
| 1020 |
+
{
|
| 1021 |
+
"entropy": 0.4857471022754908,
|
| 1022 |
+
"epoch": 2.4383561643835616,
|
| 1023 |
+
"grad_norm": 0.9696341753005981,
|
| 1024 |
+
"learning_rate": 0.0001891668789070541,
|
| 1025 |
+
"loss": 0.4149796962738037,
|
| 1026 |
+
"mean_token_accuracy": 0.8704176343977451,
|
| 1027 |
+
"num_tokens": 2286283.0,
|
| 1028 |
+
"step": 980
|
| 1029 |
+
},
|
| 1030 |
+
{
|
| 1031 |
+
"epoch": 2.4383561643835616,
|
| 1032 |
+
"eval_entropy": 0.4872790058684904,
|
| 1033 |
+
"eval_loss": 0.5412707924842834,
|
| 1034 |
+
"eval_mean_token_accuracy": 0.8509329602468846,
|
| 1035 |
+
"eval_num_tokens": 2286283.0,
|
| 1036 |
+
"eval_runtime": 86.7846,
|
| 1037 |
+
"eval_samples_per_second": 15.855,
|
| 1038 |
+
"eval_steps_per_second": 1.982,
|
| 1039 |
+
"step": 980
|
| 1040 |
+
},
|
| 1041 |
+
{
|
| 1042 |
+
"entropy": 0.4727417893707752,
|
| 1043 |
+
"epoch": 2.488169364881694,
|
| 1044 |
+
"grad_norm": 0.7852500677108765,
|
| 1045 |
+
"learning_rate": 0.0001883129646126818,
|
| 1046 |
+
"loss": 0.4142886161804199,
|
| 1047 |
+
"mean_token_accuracy": 0.8712429471313954,
|
| 1048 |
+
"num_tokens": 2333733.0,
|
| 1049 |
+
"step": 1000
|
| 1050 |
+
},
|
| 1051 |
+
{
|
| 1052 |
+
"epoch": 2.488169364881694,
|
| 1053 |
+
"eval_entropy": 0.5386548059624295,
|
| 1054 |
+
"eval_loss": 0.536101222038269,
|
| 1055 |
+
"eval_mean_token_accuracy": 0.8499491239009902,
|
| 1056 |
+
"eval_num_tokens": 2333733.0,
|
| 1057 |
+
"eval_runtime": 86.9501,
|
| 1058 |
+
"eval_samples_per_second": 15.825,
|
| 1059 |
+
"eval_steps_per_second": 1.978,
|
| 1060 |
+
"step": 1000
|
| 1061 |
+
},
|
| 1062 |
+
{
|
| 1063 |
+
"entropy": 0.4673406321555376,
|
| 1064 |
+
"epoch": 2.5379825653798256,
|
| 1065 |
+
"grad_norm": 0.7133921384811401,
|
| 1066 |
+
"learning_rate": 0.0001874326505341286,
|
| 1067 |
+
"loss": 0.40857529640197754,
|
| 1068 |
+
"mean_token_accuracy": 0.8747925907373428,
|
| 1069 |
+
"num_tokens": 2384270.0,
|
| 1070 |
+
"step": 1020
|
| 1071 |
+
},
|
| 1072 |
+
{
|
| 1073 |
+
"epoch": 2.5379825653798256,
|
| 1074 |
+
"eval_entropy": 0.495788364909416,
|
| 1075 |
+
"eval_loss": 0.5418923497200012,
|
| 1076 |
+
"eval_mean_token_accuracy": 0.851321972040243,
|
| 1077 |
+
"eval_num_tokens": 2384270.0,
|
| 1078 |
+
"eval_runtime": 86.7154,
|
| 1079 |
+
"eval_samples_per_second": 15.868,
|
| 1080 |
+
"eval_steps_per_second": 1.983,
|
| 1081 |
+
"step": 1020
|
| 1082 |
+
},
|
| 1083 |
+
{
|
| 1084 |
+
"entropy": 0.47599745728075504,
|
| 1085 |
+
"epoch": 2.587795765877958,
|
| 1086 |
+
"grad_norm": 0.8202953338623047,
|
| 1087 |
+
"learning_rate": 0.0001865262021621137,
|
| 1088 |
+
"loss": 0.40998234748840334,
|
| 1089 |
+
"mean_token_accuracy": 0.8758242674171924,
|
| 1090 |
+
"num_tokens": 2428036.0,
|
| 1091 |
+
"step": 1040
|
| 1092 |
+
},
|
| 1093 |
+
{
|
| 1094 |
+
"epoch": 2.587795765877958,
|
| 1095 |
+
"eval_entropy": 0.4887966953737791,
|
| 1096 |
+
"eval_loss": 0.5408804416656494,
|
| 1097 |
+
"eval_mean_token_accuracy": 0.8512661065473113,
|
| 1098 |
+
"eval_num_tokens": 2428036.0,
|
| 1099 |
+
"eval_runtime": 86.7869,
|
| 1100 |
+
"eval_samples_per_second": 15.855,
|
| 1101 |
+
"eval_steps_per_second": 1.982,
|
| 1102 |
+
"step": 1040
|
| 1103 |
+
},
|
| 1104 |
+
{
|
| 1105 |
+
"entropy": 0.4824396539479494,
|
| 1106 |
+
"epoch": 2.6376089663760895,
|
| 1107 |
+
"grad_norm": 0.6507360935211182,
|
| 1108 |
+
"learning_rate": 0.00018559389286910275,
|
| 1109 |
+
"loss": 0.4165764808654785,
|
| 1110 |
+
"mean_token_accuracy": 0.8722914069890976,
|
| 1111 |
+
"num_tokens": 2476815.0,
|
| 1112 |
+
"step": 1060
|
| 1113 |
+
},
|
| 1114 |
+
{
|
| 1115 |
+
"epoch": 2.6376089663760895,
|
| 1116 |
+
"eval_entropy": 0.4793398808254752,
|
| 1117 |
+
"eval_loss": 0.5326959490776062,
|
| 1118 |
+
"eval_mean_token_accuracy": 0.8534493650807891,
|
| 1119 |
+
"eval_num_tokens": 2476815.0,
|
| 1120 |
+
"eval_runtime": 86.9559,
|
| 1121 |
+
"eval_samples_per_second": 15.824,
|
| 1122 |
+
"eval_steps_per_second": 1.978,
|
| 1123 |
+
"step": 1060
|
| 1124 |
+
},
|
| 1125 |
+
{
|
| 1126 |
+
"entropy": 0.4605010639876127,
|
| 1127 |
+
"epoch": 2.6874221668742218,
|
| 1128 |
+
"grad_norm": 0.6740535497665405,
|
| 1129 |
+
"learning_rate": 0.00018463600382686253,
|
| 1130 |
+
"loss": 0.4123940944671631,
|
| 1131 |
+
"mean_token_accuracy": 0.8733638986945153,
|
| 1132 |
+
"num_tokens": 2527131.0,
|
| 1133 |
+
"step": 1080
|
| 1134 |
+
},
|
| 1135 |
+
{
|
| 1136 |
+
"epoch": 2.6874221668742218,
|
| 1137 |
+
"eval_entropy": 0.47902208583992584,
|
| 1138 |
+
"eval_loss": 0.5372340083122253,
|
| 1139 |
+
"eval_mean_token_accuracy": 0.851325950303743,
|
| 1140 |
+
"eval_num_tokens": 2527131.0,
|
| 1141 |
+
"eval_runtime": 86.9638,
|
| 1142 |
+
"eval_samples_per_second": 15.823,
|
| 1143 |
+
"eval_steps_per_second": 1.978,
|
| 1144 |
+
"step": 1080
|
| 1145 |
+
}
|
| 1146 |
+
],
|
| 1147 |
+
"logging_steps": 20,
|
| 1148 |
+
"max_steps": 4020,
|
| 1149 |
+
"num_input_tokens_seen": 0,
|
| 1150 |
+
"num_train_epochs": 10,
|
| 1151 |
+
"save_steps": 20,
|
| 1152 |
+
"stateful_callbacks": {
|
| 1153 |
+
"TrainerControl": {
|
| 1154 |
+
"args": {
|
| 1155 |
+
"should_epoch_stop": false,
|
| 1156 |
+
"should_evaluate": false,
|
| 1157 |
+
"should_log": false,
|
| 1158 |
+
"should_save": true,
|
| 1159 |
+
"should_training_stop": false
|
| 1160 |
+
},
|
| 1161 |
+
"attributes": {}
|
| 1162 |
+
}
|
| 1163 |
+
},
|
| 1164 |
+
"total_flos": 1.0682640451304448e+17,
|
| 1165 |
+
"train_batch_size": 4,
|
| 1166 |
+
"trial_name": null,
|
| 1167 |
+
"trial_params": null
|
| 1168 |
+
}
|
overgeneralisation_original_Swedish/Qwen3.5-4B-Base_overgeneralisation_splits_original_features_train_overgeneralisation_splits_original_features_test1/checkpoint-1100/README.md
ADDED
|
@@ -0,0 +1,209 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
---
|
| 2 |
+
base_model: Qwen/Qwen3.5-4B-Base
|
| 3 |
+
library_name: peft
|
| 4 |
+
pipeline_tag: text-generation
|
| 5 |
+
tags:
|
| 6 |
+
- base_model:adapter:Qwen/Qwen3.5-4B-Base
|
| 7 |
+
- lora
|
| 8 |
+
- sft
|
| 9 |
+
- transformers
|
| 10 |
+
- trl
|
| 11 |
+
---
|
| 12 |
+
|
| 13 |
+
# Model Card for Model ID
|
| 14 |
+
|
| 15 |
+
<!-- Provide a quick summary of what the model is/does. -->
|
| 16 |
+
|
| 17 |
+
|
| 18 |
+
|
| 19 |
+
## Model Details
|
| 20 |
+
|
| 21 |
+
### Model Description
|
| 22 |
+
|
| 23 |
+
<!-- Provide a longer summary of what this model is. -->
|
| 24 |
+
|
| 25 |
+
|
| 26 |
+
|
| 27 |
+
- **Developed by:** [More Information Needed]
|
| 28 |
+
- **Funded by [optional]:** [More Information Needed]
|
| 29 |
+
- **Shared by [optional]:** [More Information Needed]
|
| 30 |
+
- **Model type:** [More Information Needed]
|
| 31 |
+
- **Language(s) (NLP):** [More Information Needed]
|
| 32 |
+
- **License:** [More Information Needed]
|
| 33 |
+
- **Finetuned from model [optional]:** [More Information Needed]
|
| 34 |
+
|
| 35 |
+
### Model Sources [optional]
|
| 36 |
+
|
| 37 |
+
<!-- Provide the basic links for the model. -->
|
| 38 |
+
|
| 39 |
+
- **Repository:** [More Information Needed]
|
| 40 |
+
- **Paper [optional]:** [More Information Needed]
|
| 41 |
+
- **Demo [optional]:** [More Information Needed]
|
| 42 |
+
|
| 43 |
+
## Uses
|
| 44 |
+
|
| 45 |
+
<!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
|
| 46 |
+
|
| 47 |
+
### Direct Use
|
| 48 |
+
|
| 49 |
+
<!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
|
| 50 |
+
|
| 51 |
+
[More Information Needed]
|
| 52 |
+
|
| 53 |
+
### Downstream Use [optional]
|
| 54 |
+
|
| 55 |
+
<!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
|
| 56 |
+
|
| 57 |
+
[More Information Needed]
|
| 58 |
+
|
| 59 |
+
### Out-of-Scope Use
|
| 60 |
+
|
| 61 |
+
<!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
|
| 62 |
+
|
| 63 |
+
[More Information Needed]
|
| 64 |
+
|
| 65 |
+
## Bias, Risks, and Limitations
|
| 66 |
+
|
| 67 |
+
<!-- This section is meant to convey both technical and sociotechnical limitations. -->
|
| 68 |
+
|
| 69 |
+
[More Information Needed]
|
| 70 |
+
|
| 71 |
+
### Recommendations
|
| 72 |
+
|
| 73 |
+
<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
|
| 74 |
+
|
| 75 |
+
Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
|
| 76 |
+
|
| 77 |
+
## How to Get Started with the Model
|
| 78 |
+
|
| 79 |
+
Use the code below to get started with the model.
|
| 80 |
+
|
| 81 |
+
[More Information Needed]
|
| 82 |
+
|
| 83 |
+
## Training Details
|
| 84 |
+
|
| 85 |
+
### Training Data
|
| 86 |
+
|
| 87 |
+
<!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
|
| 88 |
+
|
| 89 |
+
[More Information Needed]
|
| 90 |
+
|
| 91 |
+
### Training Procedure
|
| 92 |
+
|
| 93 |
+
<!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
|
| 94 |
+
|
| 95 |
+
#### Preprocessing [optional]
|
| 96 |
+
|
| 97 |
+
[More Information Needed]
|
| 98 |
+
|
| 99 |
+
|
| 100 |
+
#### Training Hyperparameters
|
| 101 |
+
|
| 102 |
+
- **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
|
| 103 |
+
|
| 104 |
+
#### Speeds, Sizes, Times [optional]
|
| 105 |
+
|
| 106 |
+
<!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
|
| 107 |
+
|
| 108 |
+
[More Information Needed]
|
| 109 |
+
|
| 110 |
+
## Evaluation
|
| 111 |
+
|
| 112 |
+
<!-- This section describes the evaluation protocols and provides the results. -->
|
| 113 |
+
|
| 114 |
+
### Testing Data, Factors & Metrics
|
| 115 |
+
|
| 116 |
+
#### Testing Data
|
| 117 |
+
|
| 118 |
+
<!-- This should link to a Dataset Card if possible. -->
|
| 119 |
+
|
| 120 |
+
[More Information Needed]
|
| 121 |
+
|
| 122 |
+
#### Factors
|
| 123 |
+
|
| 124 |
+
<!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
|
| 125 |
+
|
| 126 |
+
[More Information Needed]
|
| 127 |
+
|
| 128 |
+
#### Metrics
|
| 129 |
+
|
| 130 |
+
<!-- These are the evaluation metrics being used, ideally with a description of why. -->
|
| 131 |
+
|
| 132 |
+
[More Information Needed]
|
| 133 |
+
|
| 134 |
+
### Results
|
| 135 |
+
|
| 136 |
+
[More Information Needed]
|
| 137 |
+
|
| 138 |
+
#### Summary
|
| 139 |
+
|
| 140 |
+
|
| 141 |
+
|
| 142 |
+
## Model Examination [optional]
|
| 143 |
+
|
| 144 |
+
<!-- Relevant interpretability work for the model goes here -->
|
| 145 |
+
|
| 146 |
+
[More Information Needed]
|
| 147 |
+
|
| 148 |
+
## Environmental Impact
|
| 149 |
+
|
| 150 |
+
<!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
|
| 151 |
+
|
| 152 |
+
Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
|
| 153 |
+
|
| 154 |
+
- **Hardware Type:** [More Information Needed]
|
| 155 |
+
- **Hours used:** [More Information Needed]
|
| 156 |
+
- **Cloud Provider:** [More Information Needed]
|
| 157 |
+
- **Compute Region:** [More Information Needed]
|
| 158 |
+
- **Carbon Emitted:** [More Information Needed]
|
| 159 |
+
|
| 160 |
+
## Technical Specifications [optional]
|
| 161 |
+
|
| 162 |
+
### Model Architecture and Objective
|
| 163 |
+
|
| 164 |
+
[More Information Needed]
|
| 165 |
+
|
| 166 |
+
### Compute Infrastructure
|
| 167 |
+
|
| 168 |
+
[More Information Needed]
|
| 169 |
+
|
| 170 |
+
#### Hardware
|
| 171 |
+
|
| 172 |
+
[More Information Needed]
|
| 173 |
+
|
| 174 |
+
#### Software
|
| 175 |
+
|
| 176 |
+
[More Information Needed]
|
| 177 |
+
|
| 178 |
+
## Citation [optional]
|
| 179 |
+
|
| 180 |
+
<!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
|
| 181 |
+
|
| 182 |
+
**BibTeX:**
|
| 183 |
+
|
| 184 |
+
[More Information Needed]
|
| 185 |
+
|
| 186 |
+
**APA:**
|
| 187 |
+
|
| 188 |
+
[More Information Needed]
|
| 189 |
+
|
| 190 |
+
## Glossary [optional]
|
| 191 |
+
|
| 192 |
+
<!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
|
| 193 |
+
|
| 194 |
+
[More Information Needed]
|
| 195 |
+
|
| 196 |
+
## More Information [optional]
|
| 197 |
+
|
| 198 |
+
[More Information Needed]
|
| 199 |
+
|
| 200 |
+
## Model Card Authors [optional]
|
| 201 |
+
|
| 202 |
+
[More Information Needed]
|
| 203 |
+
|
| 204 |
+
## Model Card Contact
|
| 205 |
+
|
| 206 |
+
[More Information Needed]
|
| 207 |
+
### Framework versions
|
| 208 |
+
|
| 209 |
+
- PEFT 0.18.1
|
overgeneralisation_original_Swedish/Qwen3.5-4B-Base_overgeneralisation_splits_original_features_train_overgeneralisation_splits_original_features_test1/checkpoint-1100/adapter_config.json
ADDED
|
@@ -0,0 +1,46 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
{
|
| 2 |
+
"alora_invocation_tokens": null,
|
| 3 |
+
"alpha_pattern": {},
|
| 4 |
+
"arrow_config": null,
|
| 5 |
+
"auto_mapping": null,
|
| 6 |
+
"base_model_name_or_path": "Qwen/Qwen3.5-4B-Base",
|
| 7 |
+
"bias": "none",
|
| 8 |
+
"corda_config": null,
|
| 9 |
+
"ensure_weight_tying": false,
|
| 10 |
+
"eva_config": null,
|
| 11 |
+
"exclude_modules": null,
|
| 12 |
+
"fan_in_fan_out": false,
|
| 13 |
+
"inference_mode": true,
|
| 14 |
+
"init_lora_weights": true,
|
| 15 |
+
"layer_replication": null,
|
| 16 |
+
"layers_pattern": null,
|
| 17 |
+
"layers_to_transform": null,
|
| 18 |
+
"loftq_config": {},
|
| 19 |
+
"lora_alpha": 256,
|
| 20 |
+
"lora_bias": false,
|
| 21 |
+
"lora_dropout": 0.0005183818805460705,
|
| 22 |
+
"megatron_config": null,
|
| 23 |
+
"megatron_core": "megatron.core",
|
| 24 |
+
"modules_to_save": null,
|
| 25 |
+
"peft_type": "LORA",
|
| 26 |
+
"peft_version": "0.18.1",
|
| 27 |
+
"qalora_group_size": 16,
|
| 28 |
+
"r": 128,
|
| 29 |
+
"rank_pattern": {},
|
| 30 |
+
"revision": null,
|
| 31 |
+
"target_modules": [
|
| 32 |
+
"up_proj",
|
| 33 |
+
"q_proj",
|
| 34 |
+
"o_proj",
|
| 35 |
+
"v_proj",
|
| 36 |
+
"k_proj",
|
| 37 |
+
"gate_proj",
|
| 38 |
+
"down_proj"
|
| 39 |
+
],
|
| 40 |
+
"target_parameters": null,
|
| 41 |
+
"task_type": "CAUSAL_LM",
|
| 42 |
+
"trainable_token_indices": null,
|
| 43 |
+
"use_dora": false,
|
| 44 |
+
"use_qalora": false,
|
| 45 |
+
"use_rslora": false
|
| 46 |
+
}
|
overgeneralisation_original_Swedish/Qwen3.5-4B-Base_overgeneralisation_splits_original_features_train_overgeneralisation_splits_original_features_test1/checkpoint-1100/chat_template.jinja
ADDED
|
@@ -0,0 +1,154 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
{%- set image_count = namespace(value=0) %}
|
| 2 |
+
{%- set video_count = namespace(value=0) %}
|
| 3 |
+
{%- macro render_content(content, do_vision_count, is_system_content=false) %}
|
| 4 |
+
{%- if content is string %}
|
| 5 |
+
{{- content }}
|
| 6 |
+
{%- elif content is iterable and content is not mapping %}
|
| 7 |
+
{%- for item in content %}
|
| 8 |
+
{%- if 'image' in item or 'image_url' in item or item.type == 'image' %}
|
| 9 |
+
{%- if is_system_content %}
|
| 10 |
+
{{- raise_exception('System message cannot contain images.') }}
|
| 11 |
+
{%- endif %}
|
| 12 |
+
{%- if do_vision_count %}
|
| 13 |
+
{%- set image_count.value = image_count.value + 1 %}
|
| 14 |
+
{%- endif %}
|
| 15 |
+
{%- if add_vision_id %}
|
| 16 |
+
{{- 'Picture ' ~ image_count.value ~ ': ' }}
|
| 17 |
+
{%- endif %}
|
| 18 |
+
{{- '<|vision_start|><|image_pad|><|vision_end|>' }}
|
| 19 |
+
{%- elif 'video' in item or item.type == 'video' %}
|
| 20 |
+
{%- if is_system_content %}
|
| 21 |
+
{{- raise_exception('System message cannot contain videos.') }}
|
| 22 |
+
{%- endif %}
|
| 23 |
+
{%- if do_vision_count %}
|
| 24 |
+
{%- set video_count.value = video_count.value + 1 %}
|
| 25 |
+
{%- endif %}
|
| 26 |
+
{%- if add_vision_id %}
|
| 27 |
+
{{- 'Video ' ~ video_count.value ~ ': ' }}
|
| 28 |
+
{%- endif %}
|
| 29 |
+
{{- '<|vision_start|><|video_pad|><|vision_end|>' }}
|
| 30 |
+
{%- elif 'text' in item %}
|
| 31 |
+
{{- item.text }}
|
| 32 |
+
{%- else %}
|
| 33 |
+
{{- raise_exception('Unexpected item type in content.') }}
|
| 34 |
+
{%- endif %}
|
| 35 |
+
{%- endfor %}
|
| 36 |
+
{%- elif content is none or content is undefined %}
|
| 37 |
+
{{- '' }}
|
| 38 |
+
{%- else %}
|
| 39 |
+
{{- raise_exception('Unexpected content type.') }}
|
| 40 |
+
{%- endif %}
|
| 41 |
+
{%- endmacro %}
|
| 42 |
+
{%- if not messages %}
|
| 43 |
+
{{- raise_exception('No messages provided.') }}
|
| 44 |
+
{%- endif %}
|
| 45 |
+
{%- if tools and tools is iterable and tools is not mapping %}
|
| 46 |
+
{{- '<|im_start|>system\n' }}
|
| 47 |
+
{{- "# Tools\n\nYou have access to the following functions:\n\n<tools>" }}
|
| 48 |
+
{%- for tool in tools %}
|
| 49 |
+
{{- "\n" }}
|
| 50 |
+
{{- tool | tojson }}
|
| 51 |
+
{%- endfor %}
|
| 52 |
+
{{- "\n</tools>" }}
|
| 53 |
+
{{- '\n\nIf you choose to call a function ONLY reply in the following format with NO suffix:\n\n<tool_call>\n<function=example_function_name>\n<parameter=example_parameter_1>\nvalue_1\n</parameter>\n<parameter=example_parameter_2>\nThis is the value for the second parameter\nthat can span\nmultiple lines\n</parameter>\n</function>\n</tool_call>\n\n<IMPORTANT>\nReminder:\n- Function calls MUST follow the specified format: an inner <function=...></function> block must be nested within <tool_call></tool_call> XML tags\n- Required parameters MUST be specified\n- You may provide optional reasoning for your function call in natural language BEFORE the function call, but NOT after\n- If there is no function call available, answer the question like normal with your current knowledge and do not tell the user about function calls\n</IMPORTANT>' }}
|
| 54 |
+
{%- if messages[0].role == 'system' %}
|
| 55 |
+
{%- set content = render_content(messages[0].content, false, true)|trim %}
|
| 56 |
+
{%- if content %}
|
| 57 |
+
{{- '\n\n' + content }}
|
| 58 |
+
{%- endif %}
|
| 59 |
+
{%- endif %}
|
| 60 |
+
{{- '<|im_end|>\n' }}
|
| 61 |
+
{%- else %}
|
| 62 |
+
{%- if messages[0].role == 'system' %}
|
| 63 |
+
{%- set content = render_content(messages[0].content, false, true)|trim %}
|
| 64 |
+
{{- '<|im_start|>system\n' + content + '<|im_end|>\n' }}
|
| 65 |
+
{%- endif %}
|
| 66 |
+
{%- endif %}
|
| 67 |
+
{%- set ns = namespace(multi_step_tool=true, last_query_index=messages|length - 1) %}
|
| 68 |
+
{%- for message in messages[::-1] %}
|
| 69 |
+
{%- set index = (messages|length - 1) - loop.index0 %}
|
| 70 |
+
{%- if ns.multi_step_tool and message.role == "user" %}
|
| 71 |
+
{%- set content = render_content(message.content, false)|trim %}
|
| 72 |
+
{%- if not(content.startswith('<tool_response>') and content.endswith('</tool_response>')) %}
|
| 73 |
+
{%- set ns.multi_step_tool = false %}
|
| 74 |
+
{%- set ns.last_query_index = index %}
|
| 75 |
+
{%- endif %}
|
| 76 |
+
{%- endif %}
|
| 77 |
+
{%- endfor %}
|
| 78 |
+
{%- if ns.multi_step_tool %}
|
| 79 |
+
{{- raise_exception('No user query found in messages.') }}
|
| 80 |
+
{%- endif %}
|
| 81 |
+
{%- for message in messages %}
|
| 82 |
+
{%- set content = render_content(message.content, true)|trim %}
|
| 83 |
+
{%- if message.role == "system" %}
|
| 84 |
+
{%- if not loop.first %}
|
| 85 |
+
{{- raise_exception('System message must be at the beginning.') }}
|
| 86 |
+
{%- endif %}
|
| 87 |
+
{%- elif message.role == "user" %}
|
| 88 |
+
{{- '<|im_start|>' + message.role + '\n' + content + '<|im_end|>' + '\n' }}
|
| 89 |
+
{%- elif message.role == "assistant" %}
|
| 90 |
+
{%- set reasoning_content = '' %}
|
| 91 |
+
{%- if message.reasoning_content is string %}
|
| 92 |
+
{%- set reasoning_content = message.reasoning_content %}
|
| 93 |
+
{%- else %}
|
| 94 |
+
{%- if '</think>' in content %}
|
| 95 |
+
{%- set reasoning_content = content.split('</think>')[0].rstrip('\n').split('<think>')[-1].lstrip('\n') %}
|
| 96 |
+
{%- set content = content.split('</think>')[-1].lstrip('\n') %}
|
| 97 |
+
{%- endif %}
|
| 98 |
+
{%- endif %}
|
| 99 |
+
{%- set reasoning_content = reasoning_content|trim %}
|
| 100 |
+
{%- if loop.index0 > ns.last_query_index %}
|
| 101 |
+
{{- '<|im_start|>' + message.role + '\n<think>\n' + reasoning_content + '\n</think>\n\n' + content }}
|
| 102 |
+
{%- else %}
|
| 103 |
+
{{- '<|im_start|>' + message.role + '\n' + content }}
|
| 104 |
+
{%- endif %}
|
| 105 |
+
{%- if message.tool_calls and message.tool_calls is iterable and message.tool_calls is not mapping %}
|
| 106 |
+
{%- for tool_call in message.tool_calls %}
|
| 107 |
+
{%- if tool_call.function is defined %}
|
| 108 |
+
{%- set tool_call = tool_call.function %}
|
| 109 |
+
{%- endif %}
|
| 110 |
+
{%- if loop.first %}
|
| 111 |
+
{%- if content|trim %}
|
| 112 |
+
{{- '\n\n<tool_call>\n<function=' + tool_call.name + '>\n' }}
|
| 113 |
+
{%- else %}
|
| 114 |
+
{{- '<tool_call>\n<function=' + tool_call.name + '>\n' }}
|
| 115 |
+
{%- endif %}
|
| 116 |
+
{%- else %}
|
| 117 |
+
{{- '\n<tool_call>\n<function=' + tool_call.name + '>\n' }}
|
| 118 |
+
{%- endif %}
|
| 119 |
+
{%- if tool_call.arguments is defined %}
|
| 120 |
+
{%- for args_name, args_value in tool_call.arguments|items %}
|
| 121 |
+
{{- '<parameter=' + args_name + '>\n' }}
|
| 122 |
+
{%- set args_value = args_value | tojson | safe if args_value is mapping or (args_value is sequence and args_value is not string) else args_value | string %}
|
| 123 |
+
{{- args_value }}
|
| 124 |
+
{{- '\n</parameter>\n' }}
|
| 125 |
+
{%- endfor %}
|
| 126 |
+
{%- endif %}
|
| 127 |
+
{{- '</function>\n</tool_call>' }}
|
| 128 |
+
{%- endfor %}
|
| 129 |
+
{%- endif %}
|
| 130 |
+
{{- '<|im_end|>\n' }}
|
| 131 |
+
{%- elif message.role == "tool" %}
|
| 132 |
+
{%- if loop.previtem and loop.previtem.role != "tool" %}
|
| 133 |
+
{{- '<|im_start|>user' }}
|
| 134 |
+
{%- endif %}
|
| 135 |
+
{{- '\n<tool_response>\n' }}
|
| 136 |
+
{{- content }}
|
| 137 |
+
{{- '\n</tool_response>' }}
|
| 138 |
+
{%- if not loop.last and loop.nextitem.role != "tool" %}
|
| 139 |
+
{{- '<|im_end|>\n' }}
|
| 140 |
+
{%- elif loop.last %}
|
| 141 |
+
{{- '<|im_end|>\n' }}
|
| 142 |
+
{%- endif %}
|
| 143 |
+
{%- else %}
|
| 144 |
+
{{- raise_exception('Unexpected message role.') }}
|
| 145 |
+
{%- endif %}
|
| 146 |
+
{%- endfor %}
|
| 147 |
+
{%- if add_generation_prompt %}
|
| 148 |
+
{{- '<|im_start|>assistant\n' }}
|
| 149 |
+
{%- if enable_thinking is defined and enable_thinking is false %}
|
| 150 |
+
{{- '<think>\n\n</think>\n\n' }}
|
| 151 |
+
{%- else %}
|
| 152 |
+
{{- '<think>\n' }}
|
| 153 |
+
{%- endif %}
|
| 154 |
+
{%- endif %}
|
overgeneralisation_original_Swedish/Qwen3.5-4B-Base_overgeneralisation_splits_original_features_train_overgeneralisation_splits_original_features_test1/checkpoint-1100/tokenizer_config.json
ADDED
|
@@ -0,0 +1,31 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
{
|
| 2 |
+
"add_prefix_space": false,
|
| 3 |
+
"audio_bos_token": "<|audio_start|>",
|
| 4 |
+
"audio_eos_token": "<|audio_end|>",
|
| 5 |
+
"audio_token": "<|audio_pad|>",
|
| 6 |
+
"backend": "tokenizers",
|
| 7 |
+
"bos_token": null,
|
| 8 |
+
"clean_up_tokenization_spaces": false,
|
| 9 |
+
"eos_token": "<|endoftext|>",
|
| 10 |
+
"errors": "replace",
|
| 11 |
+
"image_token": "<|image_pad|>",
|
| 12 |
+
"is_local": false,
|
| 13 |
+
"model_max_length": 262144,
|
| 14 |
+
"model_specific_special_tokens": {
|
| 15 |
+
"audio_bos_token": "<|audio_start|>",
|
| 16 |
+
"audio_eos_token": "<|audio_end|>",
|
| 17 |
+
"audio_token": "<|audio_pad|>",
|
| 18 |
+
"image_token": "<|image_pad|>",
|
| 19 |
+
"video_token": "<|video_pad|>",
|
| 20 |
+
"vision_bos_token": "<|vision_start|>",
|
| 21 |
+
"vision_eos_token": "<|vision_end|>"
|
| 22 |
+
},
|
| 23 |
+
"pad_token": "<|endoftext|>",
|
| 24 |
+
"pretokenize_regex": "(?i:'s|'t|'re|'ve|'m|'ll|'d)|[^\\r\\n\\p{L}\\p{N}]?[\\p{L}\\p{M}]+|\\p{N}| ?[^\\s\\p{L}\\p{M}\\p{N}]+[\\r\\n]*|\\s*[\\r\\n]+|\\s+(?!\\S)|\\s+",
|
| 25 |
+
"split_special_tokens": false,
|
| 26 |
+
"tokenizer_class": "TokenizersBackend",
|
| 27 |
+
"unk_token": null,
|
| 28 |
+
"video_token": "<|video_pad|>",
|
| 29 |
+
"vision_bos_token": "<|vision_start|>",
|
| 30 |
+
"vision_eos_token": "<|vision_end|>"
|
| 31 |
+
}
|
overgeneralisation_original_Swedish/Qwen3.5-4B-Base_overgeneralisation_splits_original_features_train_overgeneralisation_splits_original_features_test1/checkpoint-1100/trainer_state.json
ADDED
|
@@ -0,0 +1,1189 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
{
|
| 2 |
+
"best_global_step": null,
|
| 3 |
+
"best_metric": null,
|
| 4 |
+
"best_model_checkpoint": null,
|
| 5 |
+
"epoch": 2.7372353673723535,
|
| 6 |
+
"eval_steps": 20,
|
| 7 |
+
"global_step": 1100,
|
| 8 |
+
"is_hyper_param_search": false,
|
| 9 |
+
"is_local_process_zero": true,
|
| 10 |
+
"is_world_process_zero": true,
|
| 11 |
+
"log_history": [
|
| 12 |
+
{
|
| 13 |
+
"entropy": 1.9784346982836722,
|
| 14 |
+
"epoch": 0.049813200498132,
|
| 15 |
+
"grad_norm": 3.0229668617248535,
|
| 16 |
+
"learning_rate": 9.526142962415369e-06,
|
| 17 |
+
"loss": 1.7360023498535155,
|
| 18 |
+
"mean_token_accuracy": 0.6449888605624438,
|
| 19 |
+
"num_tokens": 46794.0,
|
| 20 |
+
"step": 20
|
| 21 |
+
},
|
| 22 |
+
{
|
| 23 |
+
"epoch": 0.049813200498132,
|
| 24 |
+
"eval_entropy": 1.41506897571475,
|
| 25 |
+
"eval_loss": 1.1876318454742432,
|
| 26 |
+
"eval_mean_token_accuracy": 0.734131895525511,
|
| 27 |
+
"eval_num_tokens": 46794.0,
|
| 28 |
+
"eval_runtime": 87.8071,
|
| 29 |
+
"eval_samples_per_second": 15.671,
|
| 30 |
+
"eval_steps_per_second": 1.959,
|
| 31 |
+
"step": 20
|
| 32 |
+
},
|
| 33 |
+
{
|
| 34 |
+
"entropy": 1.049924298375845,
|
| 35 |
+
"epoch": 0.099626400996264,
|
| 36 |
+
"grad_norm": 1.5795097351074219,
|
| 37 |
+
"learning_rate": 1.9553661870221022e-05,
|
| 38 |
+
"loss": 0.8944448471069336,
|
| 39 |
+
"mean_token_accuracy": 0.7748479396104813,
|
| 40 |
+
"num_tokens": 90754.0,
|
| 41 |
+
"step": 40
|
| 42 |
+
},
|
| 43 |
+
{
|
| 44 |
+
"epoch": 0.099626400996264,
|
| 45 |
+
"eval_entropy": 0.7996658658565476,
|
| 46 |
+
"eval_loss": 0.7202735543251038,
|
| 47 |
+
"eval_mean_token_accuracy": 0.8070558306089667,
|
| 48 |
+
"eval_num_tokens": 90754.0,
|
| 49 |
+
"eval_runtime": 86.9199,
|
| 50 |
+
"eval_samples_per_second": 15.831,
|
| 51 |
+
"eval_steps_per_second": 1.979,
|
| 52 |
+
"step": 40
|
| 53 |
+
},
|
| 54 |
+
{
|
| 55 |
+
"entropy": 0.7734908878803253,
|
| 56 |
+
"epoch": 0.149439601494396,
|
| 57 |
+
"grad_norm": 1.3136248588562012,
|
| 58 |
+
"learning_rate": 2.9581180778026673e-05,
|
| 59 |
+
"loss": 0.6780608654022217,
|
| 60 |
+
"mean_token_accuracy": 0.8168170280754566,
|
| 61 |
+
"num_tokens": 137472.0,
|
| 62 |
+
"step": 60
|
| 63 |
+
},
|
| 64 |
+
{
|
| 65 |
+
"epoch": 0.149439601494396,
|
| 66 |
+
"eval_entropy": 0.7119324009778888,
|
| 67 |
+
"eval_loss": 0.6554311513900757,
|
| 68 |
+
"eval_mean_token_accuracy": 0.8215604798738346,
|
| 69 |
+
"eval_num_tokens": 137472.0,
|
| 70 |
+
"eval_runtime": 86.8692,
|
| 71 |
+
"eval_samples_per_second": 15.84,
|
| 72 |
+
"eval_steps_per_second": 1.98,
|
| 73 |
+
"step": 60
|
| 74 |
+
},
|
| 75 |
+
{
|
| 76 |
+
"entropy": 0.7071127541363239,
|
| 77 |
+
"epoch": 0.199252801992528,
|
| 78 |
+
"grad_norm": 1.387060284614563,
|
| 79 |
+
"learning_rate": 3.960869968583232e-05,
|
| 80 |
+
"loss": 0.6382100582122803,
|
| 81 |
+
"mean_token_accuracy": 0.8229366384446621,
|
| 82 |
+
"num_tokens": 187408.0,
|
| 83 |
+
"step": 80
|
| 84 |
+
},
|
| 85 |
+
{
|
| 86 |
+
"epoch": 0.199252801992528,
|
| 87 |
+
"eval_entropy": 0.6883931482254073,
|
| 88 |
+
"eval_loss": 0.625065803527832,
|
| 89 |
+
"eval_mean_token_accuracy": 0.828940509710201,
|
| 90 |
+
"eval_num_tokens": 187408.0,
|
| 91 |
+
"eval_runtime": 86.662,
|
| 92 |
+
"eval_samples_per_second": 15.878,
|
| 93 |
+
"eval_steps_per_second": 1.985,
|
| 94 |
+
"step": 80
|
| 95 |
+
},
|
| 96 |
+
{
|
| 97 |
+
"entropy": 0.6800824083387852,
|
| 98 |
+
"epoch": 0.24906600249066002,
|
| 99 |
+
"grad_norm": 0.9892916679382324,
|
| 100 |
+
"learning_rate": 4.963621859363797e-05,
|
| 101 |
+
"loss": 0.6011715888977051,
|
| 102 |
+
"mean_token_accuracy": 0.8323964163661003,
|
| 103 |
+
"num_tokens": 234197.0,
|
| 104 |
+
"step": 100
|
| 105 |
+
},
|
| 106 |
+
{
|
| 107 |
+
"epoch": 0.24906600249066002,
|
| 108 |
+
"eval_entropy": 0.6840810470802839,
|
| 109 |
+
"eval_loss": 0.6037028431892395,
|
| 110 |
+
"eval_mean_token_accuracy": 0.8309669033732525,
|
| 111 |
+
"eval_num_tokens": 234197.0,
|
| 112 |
+
"eval_runtime": 86.4637,
|
| 113 |
+
"eval_samples_per_second": 15.914,
|
| 114 |
+
"eval_steps_per_second": 1.989,
|
| 115 |
+
"step": 100
|
| 116 |
+
},
|
| 117 |
+
{
|
| 118 |
+
"entropy": 0.6776216626167297,
|
| 119 |
+
"epoch": 0.298879202988792,
|
| 120 |
+
"grad_norm": 0.8918434977531433,
|
| 121 |
+
"learning_rate": 5.9663737501443624e-05,
|
| 122 |
+
"loss": 0.5991742610931396,
|
| 123 |
+
"mean_token_accuracy": 0.8300838828086853,
|
| 124 |
+
"num_tokens": 281241.0,
|
| 125 |
+
"step": 120
|
| 126 |
+
},
|
| 127 |
+
{
|
| 128 |
+
"epoch": 0.298879202988792,
|
| 129 |
+
"eval_entropy": 0.690427724705186,
|
| 130 |
+
"eval_loss": 0.5939701795578003,
|
| 131 |
+
"eval_mean_token_accuracy": 0.8345950186945671,
|
| 132 |
+
"eval_num_tokens": 281241.0,
|
| 133 |
+
"eval_runtime": 86.6626,
|
| 134 |
+
"eval_samples_per_second": 15.878,
|
| 135 |
+
"eval_steps_per_second": 1.985,
|
| 136 |
+
"step": 120
|
| 137 |
+
},
|
| 138 |
+
{
|
| 139 |
+
"entropy": 0.6709842771291733,
|
| 140 |
+
"epoch": 0.34869240348692404,
|
| 141 |
+
"grad_norm": 0.9135531187057495,
|
| 142 |
+
"learning_rate": 6.969125640924927e-05,
|
| 143 |
+
"loss": 0.5914147377014161,
|
| 144 |
+
"mean_token_accuracy": 0.8314545609056949,
|
| 145 |
+
"num_tokens": 327393.0,
|
| 146 |
+
"step": 140
|
| 147 |
+
},
|
| 148 |
+
{
|
| 149 |
+
"epoch": 0.34869240348692404,
|
| 150 |
+
"eval_entropy": 0.6584504666023476,
|
| 151 |
+
"eval_loss": 0.5849721431732178,
|
| 152 |
+
"eval_mean_token_accuracy": 0.8357757236375365,
|
| 153 |
+
"eval_num_tokens": 327393.0,
|
| 154 |
+
"eval_runtime": 86.3262,
|
| 155 |
+
"eval_samples_per_second": 15.94,
|
| 156 |
+
"eval_steps_per_second": 1.992,
|
| 157 |
+
"step": 140
|
| 158 |
+
},
|
| 159 |
+
{
|
| 160 |
+
"entropy": 0.6524647936224938,
|
| 161 |
+
"epoch": 0.398505603985056,
|
| 162 |
+
"grad_norm": 0.8651587963104248,
|
| 163 |
+
"learning_rate": 7.971877531705493e-05,
|
| 164 |
+
"loss": 0.5710843563079834,
|
| 165 |
+
"mean_token_accuracy": 0.8396127380430698,
|
| 166 |
+
"num_tokens": 373834.0,
|
| 167 |
+
"step": 160
|
| 168 |
+
},
|
| 169 |
+
{
|
| 170 |
+
"epoch": 0.398505603985056,
|
| 171 |
+
"eval_entropy": 0.6283470298661742,
|
| 172 |
+
"eval_loss": 0.5738973617553711,
|
| 173 |
+
"eval_mean_token_accuracy": 0.8379981181649274,
|
| 174 |
+
"eval_num_tokens": 373834.0,
|
| 175 |
+
"eval_runtime": 86.5619,
|
| 176 |
+
"eval_samples_per_second": 15.896,
|
| 177 |
+
"eval_steps_per_second": 1.987,
|
| 178 |
+
"step": 160
|
| 179 |
+
},
|
| 180 |
+
{
|
| 181 |
+
"entropy": 0.6450445972383022,
|
| 182 |
+
"epoch": 0.44831880448318806,
|
| 183 |
+
"grad_norm": 0.8661723732948303,
|
| 184 |
+
"learning_rate": 8.974629422486058e-05,
|
| 185 |
+
"loss": 0.5677794933319091,
|
| 186 |
+
"mean_token_accuracy": 0.8389350369572639,
|
| 187 |
+
"num_tokens": 422572.0,
|
| 188 |
+
"step": 180
|
| 189 |
+
},
|
| 190 |
+
{
|
| 191 |
+
"epoch": 0.44831880448318806,
|
| 192 |
+
"eval_entropy": 0.6142613257086554,
|
| 193 |
+
"eval_loss": 0.5698265433311462,
|
| 194 |
+
"eval_mean_token_accuracy": 0.8388577273418737,
|
| 195 |
+
"eval_num_tokens": 422572.0,
|
| 196 |
+
"eval_runtime": 86.4443,
|
| 197 |
+
"eval_samples_per_second": 15.918,
|
| 198 |
+
"eval_steps_per_second": 1.99,
|
| 199 |
+
"step": 180
|
| 200 |
+
},
|
| 201 |
+
{
|
| 202 |
+
"entropy": 0.6448334597051144,
|
| 203 |
+
"epoch": 0.49813200498132004,
|
| 204 |
+
"grad_norm": 0.9662242531776428,
|
| 205 |
+
"learning_rate": 9.977381313266624e-05,
|
| 206 |
+
"loss": 0.581433916091919,
|
| 207 |
+
"mean_token_accuracy": 0.8387043006718159,
|
| 208 |
+
"num_tokens": 471879.0,
|
| 209 |
+
"step": 200
|
| 210 |
+
},
|
| 211 |
+
{
|
| 212 |
+
"epoch": 0.49813200498132004,
|
| 213 |
+
"eval_entropy": 0.6154296522916749,
|
| 214 |
+
"eval_loss": 0.5660303831100464,
|
| 215 |
+
"eval_mean_token_accuracy": 0.8412494766850804,
|
| 216 |
+
"eval_num_tokens": 471879.0,
|
| 217 |
+
"eval_runtime": 86.3063,
|
| 218 |
+
"eval_samples_per_second": 15.943,
|
| 219 |
+
"eval_steps_per_second": 1.993,
|
| 220 |
+
"step": 200
|
| 221 |
+
},
|
| 222 |
+
{
|
| 223 |
+
"entropy": 0.6376728117465973,
|
| 224 |
+
"epoch": 0.547945205479452,
|
| 225 |
+
"grad_norm": 0.7618638873100281,
|
| 226 |
+
"learning_rate": 0.00010980133204047189,
|
| 227 |
+
"loss": 0.5678351402282715,
|
| 228 |
+
"mean_token_accuracy": 0.8404546812176704,
|
| 229 |
+
"num_tokens": 520984.0,
|
| 230 |
+
"step": 220
|
| 231 |
+
},
|
| 232 |
+
{
|
| 233 |
+
"epoch": 0.547945205479452,
|
| 234 |
+
"eval_entropy": 0.6181817033956217,
|
| 235 |
+
"eval_loss": 0.5663750171661377,
|
| 236 |
+
"eval_mean_token_accuracy": 0.8388350962899452,
|
| 237 |
+
"eval_num_tokens": 520984.0,
|
| 238 |
+
"eval_runtime": 86.5904,
|
| 239 |
+
"eval_samples_per_second": 15.891,
|
| 240 |
+
"eval_steps_per_second": 1.986,
|
| 241 |
+
"step": 220
|
| 242 |
+
},
|
| 243 |
+
{
|
| 244 |
+
"entropy": 0.6303176879882812,
|
| 245 |
+
"epoch": 0.597758405977584,
|
| 246 |
+
"grad_norm": 0.7571695446968079,
|
| 247 |
+
"learning_rate": 0.00011982885094827753,
|
| 248 |
+
"loss": 0.5502778053283691,
|
| 249 |
+
"mean_token_accuracy": 0.8429657347500324,
|
| 250 |
+
"num_tokens": 566596.0,
|
| 251 |
+
"step": 240
|
| 252 |
+
},
|
| 253 |
+
{
|
| 254 |
+
"epoch": 0.597758405977584,
|
| 255 |
+
"eval_entropy": 0.6252533817707107,
|
| 256 |
+
"eval_loss": 0.5570284128189087,
|
| 257 |
+
"eval_mean_token_accuracy": 0.8427327847064927,
|
| 258 |
+
"eval_num_tokens": 566596.0,
|
| 259 |
+
"eval_runtime": 86.4157,
|
| 260 |
+
"eval_samples_per_second": 15.923,
|
| 261 |
+
"eval_steps_per_second": 1.99,
|
| 262 |
+
"step": 240
|
| 263 |
+
},
|
| 264 |
+
{
|
| 265 |
+
"entropy": 0.6202544964849949,
|
| 266 |
+
"epoch": 0.6475716064757161,
|
| 267 |
+
"grad_norm": 0.6447190642356873,
|
| 268 |
+
"learning_rate": 0.00012985636985608318,
|
| 269 |
+
"loss": 0.5485352993011474,
|
| 270 |
+
"mean_token_accuracy": 0.844165726006031,
|
| 271 |
+
"num_tokens": 613603.0,
|
| 272 |
+
"step": 260
|
| 273 |
+
},
|
| 274 |
+
{
|
| 275 |
+
"epoch": 0.6475716064757161,
|
| 276 |
+
"eval_entropy": 0.6441633552312851,
|
| 277 |
+
"eval_loss": 0.5606644153594971,
|
| 278 |
+
"eval_mean_token_accuracy": 0.842403513054515,
|
| 279 |
+
"eval_num_tokens": 613603.0,
|
| 280 |
+
"eval_runtime": 86.6343,
|
| 281 |
+
"eval_samples_per_second": 15.883,
|
| 282 |
+
"eval_steps_per_second": 1.985,
|
| 283 |
+
"step": 260
|
| 284 |
+
},
|
| 285 |
+
{
|
| 286 |
+
"entropy": 0.6306711677461863,
|
| 287 |
+
"epoch": 0.6973848069738481,
|
| 288 |
+
"grad_norm": 0.7869907021522522,
|
| 289 |
+
"learning_rate": 0.00013988388876388883,
|
| 290 |
+
"loss": 0.5579307556152344,
|
| 291 |
+
"mean_token_accuracy": 0.841247134655714,
|
| 292 |
+
"num_tokens": 658565.0,
|
| 293 |
+
"step": 280
|
| 294 |
+
},
|
| 295 |
+
{
|
| 296 |
+
"epoch": 0.6973848069738481,
|
| 297 |
+
"eval_entropy": 0.6263934678809587,
|
| 298 |
+
"eval_loss": 0.5559113025665283,
|
| 299 |
+
"eval_mean_token_accuracy": 0.8427334743183713,
|
| 300 |
+
"eval_num_tokens": 658565.0,
|
| 301 |
+
"eval_runtime": 86.6403,
|
| 302 |
+
"eval_samples_per_second": 15.882,
|
| 303 |
+
"eval_steps_per_second": 1.985,
|
| 304 |
+
"step": 280
|
| 305 |
+
},
|
| 306 |
+
{
|
| 307 |
+
"entropy": 0.6385872110724449,
|
| 308 |
+
"epoch": 0.7471980074719801,
|
| 309 |
+
"grad_norm": 0.6679229736328125,
|
| 310 |
+
"learning_rate": 0.0001499114076716945,
|
| 311 |
+
"loss": 0.5667279720306396,
|
| 312 |
+
"mean_token_accuracy": 0.8389136254787445,
|
| 313 |
+
"num_tokens": 705680.0,
|
| 314 |
+
"step": 300
|
| 315 |
+
},
|
| 316 |
+
{
|
| 317 |
+
"epoch": 0.7471980074719801,
|
| 318 |
+
"eval_entropy": 0.6141417321077612,
|
| 319 |
+
"eval_loss": 0.5570600628852844,
|
| 320 |
+
"eval_mean_token_accuracy": 0.8437647996253745,
|
| 321 |
+
"eval_num_tokens": 705680.0,
|
| 322 |
+
"eval_runtime": 86.7588,
|
| 323 |
+
"eval_samples_per_second": 15.86,
|
| 324 |
+
"eval_steps_per_second": 1.983,
|
| 325 |
+
"step": 300
|
| 326 |
+
},
|
| 327 |
+
{
|
| 328 |
+
"entropy": 0.6199494235217571,
|
| 329 |
+
"epoch": 0.797011207970112,
|
| 330 |
+
"grad_norm": 0.7924400568008423,
|
| 331 |
+
"learning_rate": 0.00015993892657950015,
|
| 332 |
+
"loss": 0.5529299736022949,
|
| 333 |
+
"mean_token_accuracy": 0.8426973208785057,
|
| 334 |
+
"num_tokens": 752616.0,
|
| 335 |
+
"step": 320
|
| 336 |
+
},
|
| 337 |
+
{
|
| 338 |
+
"epoch": 0.797011207970112,
|
| 339 |
+
"eval_entropy": 0.6133768925833147,
|
| 340 |
+
"eval_loss": 0.556602418422699,
|
| 341 |
+
"eval_mean_token_accuracy": 0.8432947965555413,
|
| 342 |
+
"eval_num_tokens": 752616.0,
|
| 343 |
+
"eval_runtime": 86.492,
|
| 344 |
+
"eval_samples_per_second": 15.909,
|
| 345 |
+
"eval_steps_per_second": 1.989,
|
| 346 |
+
"step": 320
|
| 347 |
+
},
|
| 348 |
+
{
|
| 349 |
+
"entropy": 0.6203986253589392,
|
| 350 |
+
"epoch": 0.8468244084682441,
|
| 351 |
+
"grad_norm": 0.8364354372024536,
|
| 352 |
+
"learning_rate": 0.00016996644548730578,
|
| 353 |
+
"loss": 0.5551144123077393,
|
| 354 |
+
"mean_token_accuracy": 0.8432973213493824,
|
| 355 |
+
"num_tokens": 797151.0,
|
| 356 |
+
"step": 340
|
| 357 |
+
},
|
| 358 |
+
{
|
| 359 |
+
"epoch": 0.8468244084682441,
|
| 360 |
+
"eval_entropy": 0.6017442844634833,
|
| 361 |
+
"eval_loss": 0.5566568374633789,
|
| 362 |
+
"eval_mean_token_accuracy": 0.8437666123689607,
|
| 363 |
+
"eval_num_tokens": 797151.0,
|
| 364 |
+
"eval_runtime": 86.5552,
|
| 365 |
+
"eval_samples_per_second": 15.897,
|
| 366 |
+
"eval_steps_per_second": 1.987,
|
| 367 |
+
"step": 340
|
| 368 |
+
},
|
| 369 |
+
{
|
| 370 |
+
"entropy": 0.6341533534228802,
|
| 371 |
+
"epoch": 0.8966376089663761,
|
| 372 |
+
"grad_norm": 0.7783445715904236,
|
| 373 |
+
"learning_rate": 0.00017999396439511144,
|
| 374 |
+
"loss": 0.5669133186340332,
|
| 375 |
+
"mean_token_accuracy": 0.8379446342587471,
|
| 376 |
+
"num_tokens": 843585.0,
|
| 377 |
+
"step": 360
|
| 378 |
+
},
|
| 379 |
+
{
|
| 380 |
+
"epoch": 0.8966376089663761,
|
| 381 |
+
"eval_entropy": 0.6055107958788095,
|
| 382 |
+
"eval_loss": 0.5599350333213806,
|
| 383 |
+
"eval_mean_token_accuracy": 0.8435030894917112,
|
| 384 |
+
"eval_num_tokens": 843585.0,
|
| 385 |
+
"eval_runtime": 86.4814,
|
| 386 |
+
"eval_samples_per_second": 15.911,
|
| 387 |
+
"eval_steps_per_second": 1.989,
|
| 388 |
+
"step": 360
|
| 389 |
+
},
|
| 390 |
+
{
|
| 391 |
+
"entropy": 0.6306198488920927,
|
| 392 |
+
"epoch": 0.9464508094645081,
|
| 393 |
+
"grad_norm": 0.8449786901473999,
|
| 394 |
+
"learning_rate": 0.0001900214833029171,
|
| 395 |
+
"loss": 0.5739435195922852,
|
| 396 |
+
"mean_token_accuracy": 0.8393832489848136,
|
| 397 |
+
"num_tokens": 889842.0,
|
| 398 |
+
"step": 380
|
| 399 |
+
},
|
| 400 |
+
{
|
| 401 |
+
"epoch": 0.9464508094645081,
|
| 402 |
+
"eval_entropy": 0.6129532439071078,
|
| 403 |
+
"eval_loss": 0.5566295981407166,
|
| 404 |
+
"eval_mean_token_accuracy": 0.8430350880290187,
|
| 405 |
+
"eval_num_tokens": 889842.0,
|
| 406 |
+
"eval_runtime": 86.4643,
|
| 407 |
+
"eval_samples_per_second": 15.914,
|
| 408 |
+
"eval_steps_per_second": 1.989,
|
| 409 |
+
"step": 380
|
| 410 |
+
},
|
| 411 |
+
{
|
| 412 |
+
"entropy": 0.6203123550862074,
|
| 413 |
+
"epoch": 0.9962640099626401,
|
| 414 |
+
"grad_norm": 0.7334314584732056,
|
| 415 |
+
"learning_rate": 0.00020004900221072276,
|
| 416 |
+
"loss": 0.5547565937042236,
|
| 417 |
+
"mean_token_accuracy": 0.8403573960065842,
|
| 418 |
+
"num_tokens": 935589.0,
|
| 419 |
+
"step": 400
|
| 420 |
+
},
|
| 421 |
+
{
|
| 422 |
+
"epoch": 0.9962640099626401,
|
| 423 |
+
"eval_entropy": 0.6275761647279873,
|
| 424 |
+
"eval_loss": 0.5621116757392883,
|
| 425 |
+
"eval_mean_token_accuracy": 0.841587379228237,
|
| 426 |
+
"eval_num_tokens": 935589.0,
|
| 427 |
+
"eval_runtime": 86.4748,
|
| 428 |
+
"eval_samples_per_second": 15.912,
|
| 429 |
+
"eval_steps_per_second": 1.989,
|
| 430 |
+
"step": 400
|
| 431 |
+
},
|
| 432 |
+
{
|
| 433 |
+
"entropy": 0.5795013002860241,
|
| 434 |
+
"epoch": 1.0448318804483188,
|
| 435 |
+
"grad_norm": 0.8858296871185303,
|
| 436 |
+
"learning_rate": 0.0002015421505577756,
|
| 437 |
+
"loss": 0.5183939933776855,
|
| 438 |
+
"mean_token_accuracy": 0.850081592034071,
|
| 439 |
+
"num_tokens": 980589.0,
|
| 440 |
+
"step": 420
|
| 441 |
+
},
|
| 442 |
+
{
|
| 443 |
+
"epoch": 1.0448318804483188,
|
| 444 |
+
"eval_entropy": 0.5583065545489622,
|
| 445 |
+
"eval_loss": 0.5605642199516296,
|
| 446 |
+
"eval_mean_token_accuracy": 0.8439708411000496,
|
| 447 |
+
"eval_num_tokens": 980589.0,
|
| 448 |
+
"eval_runtime": 86.5422,
|
| 449 |
+
"eval_samples_per_second": 15.9,
|
| 450 |
+
"eval_steps_per_second": 1.987,
|
| 451 |
+
"step": 420
|
| 452 |
+
},
|
| 453 |
+
{
|
| 454 |
+
"entropy": 0.5671238023787737,
|
| 455 |
+
"epoch": 1.0946450809464507,
|
| 456 |
+
"grad_norm": 0.6882498264312744,
|
| 457 |
+
"learning_rate": 0.00020150112347025443,
|
| 458 |
+
"loss": 0.5077326774597168,
|
| 459 |
+
"mean_token_accuracy": 0.8489868573844432,
|
| 460 |
+
"num_tokens": 1027852.0,
|
| 461 |
+
"step": 440
|
| 462 |
+
},
|
| 463 |
+
{
|
| 464 |
+
"epoch": 1.0946450809464507,
|
| 465 |
+
"eval_entropy": 0.5868900277933409,
|
| 466 |
+
"eval_loss": 0.5602695345878601,
|
| 467 |
+
"eval_mean_token_accuracy": 0.8428842161977014,
|
| 468 |
+
"eval_num_tokens": 1027852.0,
|
| 469 |
+
"eval_runtime": 86.623,
|
| 470 |
+
"eval_samples_per_second": 15.885,
|
| 471 |
+
"eval_steps_per_second": 1.986,
|
| 472 |
+
"step": 440
|
| 473 |
+
},
|
| 474 |
+
{
|
| 475 |
+
"entropy": 0.5533561781048775,
|
| 476 |
+
"epoch": 1.1444582814445827,
|
| 477 |
+
"grad_norm": 0.7717723250389099,
|
| 478 |
+
"learning_rate": 0.0002014297192297181,
|
| 479 |
+
"loss": 0.4954517364501953,
|
| 480 |
+
"mean_token_accuracy": 0.8529035650193691,
|
| 481 |
+
"num_tokens": 1077649.0,
|
| 482 |
+
"step": 460
|
| 483 |
+
},
|
| 484 |
+
{
|
| 485 |
+
"epoch": 1.1444582814445827,
|
| 486 |
+
"eval_entropy": 0.5600803743961246,
|
| 487 |
+
"eval_loss": 0.5608077645301819,
|
| 488 |
+
"eval_mean_token_accuracy": 0.8445036771685578,
|
| 489 |
+
"eval_num_tokens": 1077649.0,
|
| 490 |
+
"eval_runtime": 86.1316,
|
| 491 |
+
"eval_samples_per_second": 15.976,
|
| 492 |
+
"eval_steps_per_second": 1.997,
|
| 493 |
+
"step": 460
|
| 494 |
+
},
|
| 495 |
+
{
|
| 496 |
+
"entropy": 0.5692154694348573,
|
| 497 |
+
"epoch": 1.1942714819427147,
|
| 498 |
+
"grad_norm": 0.7322827577590942,
|
| 499 |
+
"learning_rate": 0.0002013279593707117,
|
| 500 |
+
"loss": 0.505049467086792,
|
| 501 |
+
"mean_token_accuracy": 0.8551576808094978,
|
| 502 |
+
"num_tokens": 1124872.0,
|
| 503 |
+
"step": 480
|
| 504 |
+
},
|
| 505 |
+
{
|
| 506 |
+
"epoch": 1.1942714819427147,
|
| 507 |
+
"eval_entropy": 0.5732695829383162,
|
| 508 |
+
"eval_loss": 0.5594323873519897,
|
| 509 |
+
"eval_mean_token_accuracy": 0.8449713407560836,
|
| 510 |
+
"eval_num_tokens": 1124872.0,
|
| 511 |
+
"eval_runtime": 86.2726,
|
| 512 |
+
"eval_samples_per_second": 15.949,
|
| 513 |
+
"eval_steps_per_second": 1.994,
|
| 514 |
+
"step": 480
|
| 515 |
+
},
|
| 516 |
+
{
|
| 517 |
+
"entropy": 0.5817618492990733,
|
| 518 |
+
"epoch": 1.244084682440847,
|
| 519 |
+
"grad_norm": 1.1776764392852783,
|
| 520 |
+
"learning_rate": 0.0002011958745826208,
|
| 521 |
+
"loss": 0.5137609958648681,
|
| 522 |
+
"mean_token_accuracy": 0.8521522544324398,
|
| 523 |
+
"num_tokens": 1168698.0,
|
| 524 |
+
"step": 500
|
| 525 |
+
},
|
| 526 |
+
{
|
| 527 |
+
"epoch": 1.244084682440847,
|
| 528 |
+
"eval_entropy": 0.5662581343636957,
|
| 529 |
+
"eval_loss": 0.5595026016235352,
|
| 530 |
+
"eval_mean_token_accuracy": 0.8441977164773053,
|
| 531 |
+
"eval_num_tokens": 1168698.0,
|
| 532 |
+
"eval_runtime": 86.7261,
|
| 533 |
+
"eval_samples_per_second": 15.866,
|
| 534 |
+
"eval_steps_per_second": 1.983,
|
| 535 |
+
"step": 500
|
| 536 |
+
},
|
| 537 |
+
{
|
| 538 |
+
"entropy": 0.5712925456464291,
|
| 539 |
+
"epoch": 1.293897882938979,
|
| 540 |
+
"grad_norm": 0.7960361838340759,
|
| 541 |
+
"learning_rate": 0.0002010335047004159,
|
| 542 |
+
"loss": 0.5134767532348633,
|
| 543 |
+
"mean_token_accuracy": 0.8513577707111836,
|
| 544 |
+
"num_tokens": 1216679.0,
|
| 545 |
+
"step": 520
|
| 546 |
+
},
|
| 547 |
+
{
|
| 548 |
+
"epoch": 1.293897882938979,
|
| 549 |
+
"eval_entropy": 0.5441222797299541,
|
| 550 |
+
"eval_loss": 0.5535460114479065,
|
| 551 |
+
"eval_mean_token_accuracy": 0.8450886118550633,
|
| 552 |
+
"eval_num_tokens": 1216679.0,
|
| 553 |
+
"eval_runtime": 86.2675,
|
| 554 |
+
"eval_samples_per_second": 15.95,
|
| 555 |
+
"eval_steps_per_second": 1.994,
|
| 556 |
+
"step": 520
|
| 557 |
+
},
|
| 558 |
+
{
|
| 559 |
+
"entropy": 0.5787045754492283,
|
| 560 |
+
"epoch": 1.3437110834371109,
|
| 561 |
+
"grad_norm": 0.9205410480499268,
|
| 562 |
+
"learning_rate": 0.00020084089869263887,
|
| 563 |
+
"loss": 0.5119701862335205,
|
| 564 |
+
"mean_token_accuracy": 0.8503516331315041,
|
| 565 |
+
"num_tokens": 1261365.0,
|
| 566 |
+
"step": 540
|
| 567 |
+
},
|
| 568 |
+
{
|
| 569 |
+
"epoch": 1.3437110834371109,
|
| 570 |
+
"eval_entropy": 0.5744457827057949,
|
| 571 |
+
"eval_loss": 0.5514978766441345,
|
| 572 |
+
"eval_mean_token_accuracy": 0.845929987901865,
|
| 573 |
+
"eval_num_tokens": 1261365.0,
|
| 574 |
+
"eval_runtime": 86.2299,
|
| 575 |
+
"eval_samples_per_second": 15.957,
|
| 576 |
+
"eval_steps_per_second": 1.995,
|
| 577 |
+
"step": 540
|
| 578 |
+
},
|
| 579 |
+
{
|
| 580 |
+
"entropy": 0.5739392962306737,
|
| 581 |
+
"epoch": 1.3935242839352429,
|
| 582 |
+
"grad_norm": 0.7475653886795044,
|
| 583 |
+
"learning_rate": 0.00020061811464663464,
|
| 584 |
+
"loss": 0.5189042091369629,
|
| 585 |
+
"mean_token_accuracy": 0.8492388024926185,
|
| 586 |
+
"num_tokens": 1306879.0,
|
| 587 |
+
"step": 560
|
| 588 |
+
},
|
| 589 |
+
{
|
| 590 |
+
"epoch": 1.3935242839352429,
|
| 591 |
+
"eval_entropy": 0.6116398271433142,
|
| 592 |
+
"eval_loss": 0.551732063293457,
|
| 593 |
+
"eval_mean_token_accuracy": 0.8450756967067719,
|
| 594 |
+
"eval_num_tokens": 1306879.0,
|
| 595 |
+
"eval_runtime": 86.6081,
|
| 596 |
+
"eval_samples_per_second": 15.888,
|
| 597 |
+
"eval_steps_per_second": 1.986,
|
| 598 |
+
"step": 560
|
| 599 |
+
},
|
| 600 |
+
{
|
| 601 |
+
"entropy": 0.5755622573196888,
|
| 602 |
+
"epoch": 1.4433374844333748,
|
| 603 |
+
"grad_norm": 0.8218411803245544,
|
| 604 |
+
"learning_rate": 0.00020036521975103286,
|
| 605 |
+
"loss": 0.5106248378753662,
|
| 606 |
+
"mean_token_accuracy": 0.8506785586476326,
|
| 607 |
+
"num_tokens": 1353534.0,
|
| 608 |
+
"step": 580
|
| 609 |
+
},
|
| 610 |
+
{
|
| 611 |
+
"epoch": 1.4433374844333748,
|
| 612 |
+
"eval_entropy": 0.5906928708386976,
|
| 613 |
+
"eval_loss": 0.551278829574585,
|
| 614 |
+
"eval_mean_token_accuracy": 0.8462819308042526,
|
| 615 |
+
"eval_num_tokens": 1353534.0,
|
| 616 |
+
"eval_runtime": 86.5438,
|
| 617 |
+
"eval_samples_per_second": 15.899,
|
| 618 |
+
"eval_steps_per_second": 1.987,
|
| 619 |
+
"step": 580
|
| 620 |
+
},
|
| 621 |
+
{
|
| 622 |
+
"entropy": 0.5694822132587433,
|
| 623 |
+
"epoch": 1.4931506849315068,
|
| 624 |
+
"grad_norm": 0.8880652189254761,
|
| 625 |
+
"learning_rate": 0.00020008229027548475,
|
| 626 |
+
"loss": 0.5140334606170655,
|
| 627 |
+
"mean_token_accuracy": 0.8521522797644139,
|
| 628 |
+
"num_tokens": 1399537.0,
|
| 629 |
+
"step": 600
|
| 630 |
+
},
|
| 631 |
+
{
|
| 632 |
+
"epoch": 1.4931506849315068,
|
| 633 |
+
"eval_entropy": 0.5599641964532608,
|
| 634 |
+
"eval_loss": 0.5501875877380371,
|
| 635 |
+
"eval_mean_token_accuracy": 0.8467660788879838,
|
| 636 |
+
"eval_num_tokens": 1399537.0,
|
| 637 |
+
"eval_runtime": 86.6458,
|
| 638 |
+
"eval_samples_per_second": 15.881,
|
| 639 |
+
"eval_steps_per_second": 1.985,
|
| 640 |
+
"step": 600
|
| 641 |
+
},
|
| 642 |
+
{
|
| 643 |
+
"entropy": 0.5675108034163714,
|
| 644 |
+
"epoch": 1.5429638854296388,
|
| 645 |
+
"grad_norm": 0.837087094783783,
|
| 646 |
+
"learning_rate": 0.0001997694115476612,
|
| 647 |
+
"loss": 0.5099846363067627,
|
| 648 |
+
"mean_token_accuracy": 0.8543680295348167,
|
| 649 |
+
"num_tokens": 1448422.0,
|
| 650 |
+
"step": 620
|
| 651 |
+
},
|
| 652 |
+
{
|
| 653 |
+
"epoch": 1.5429638854296388,
|
| 654 |
+
"eval_entropy": 0.5728072581249614,
|
| 655 |
+
"eval_loss": 0.5445425510406494,
|
| 656 |
+
"eval_mean_token_accuracy": 0.8474342175001321,
|
| 657 |
+
"eval_num_tokens": 1448422.0,
|
| 658 |
+
"eval_runtime": 86.4859,
|
| 659 |
+
"eval_samples_per_second": 15.91,
|
| 660 |
+
"eval_steps_per_second": 1.989,
|
| 661 |
+
"step": 620
|
| 662 |
+
},
|
| 663 |
+
{
|
| 664 |
+
"entropy": 0.5700885068625212,
|
| 665 |
+
"epoch": 1.592777085927771,
|
| 666 |
+
"grad_norm": 0.6598765850067139,
|
| 667 |
+
"learning_rate": 0.000199426677927519,
|
| 668 |
+
"loss": 0.5122694969177246,
|
| 669 |
+
"mean_token_accuracy": 0.8519927568733692,
|
| 670 |
+
"num_tokens": 1495009.0,
|
| 671 |
+
"step": 640
|
| 672 |
+
},
|
| 673 |
+
{
|
| 674 |
+
"epoch": 1.592777085927771,
|
| 675 |
+
"eval_entropy": 0.5476993622128353,
|
| 676 |
+
"eval_loss": 0.5427973866462708,
|
| 677 |
+
"eval_mean_token_accuracy": 0.8478512147138285,
|
| 678 |
+
"eval_num_tokens": 1495009.0,
|
| 679 |
+
"eval_runtime": 86.4172,
|
| 680 |
+
"eval_samples_per_second": 15.923,
|
| 681 |
+
"eval_steps_per_second": 1.99,
|
| 682 |
+
"step": 640
|
| 683 |
+
},
|
| 684 |
+
{
|
| 685 |
+
"entropy": 0.5829229176044464,
|
| 686 |
+
"epoch": 1.6425902864259028,
|
| 687 |
+
"grad_norm": 0.6965194940567017,
|
| 688 |
+
"learning_rate": 0.00019905419277884342,
|
| 689 |
+
"loss": 0.5253659725189209,
|
| 690 |
+
"mean_token_accuracy": 0.8493309423327446,
|
| 691 |
+
"num_tokens": 1536932.0,
|
| 692 |
+
"step": 660
|
| 693 |
+
},
|
| 694 |
+
{
|
| 695 |
+
"epoch": 1.6425902864259028,
|
| 696 |
+
"eval_entropy": 0.5666290084983028,
|
| 697 |
+
"eval_loss": 0.5467478036880493,
|
| 698 |
+
"eval_mean_token_accuracy": 0.8479407703460649,
|
| 699 |
+
"eval_num_tokens": 1536932.0,
|
| 700 |
+
"eval_runtime": 86.4414,
|
| 701 |
+
"eval_samples_per_second": 15.918,
|
| 702 |
+
"eval_steps_per_second": 1.99,
|
| 703 |
+
"step": 660
|
| 704 |
+
},
|
| 705 |
+
{
|
| 706 |
+
"entropy": 0.5498311135917902,
|
| 707 |
+
"epoch": 1.692403486924035,
|
| 708 |
+
"grad_norm": 0.636583685874939,
|
| 709 |
+
"learning_rate": 0.00019865206843807482,
|
| 710 |
+
"loss": 0.49981012344360354,
|
| 711 |
+
"mean_token_accuracy": 0.8560848504304885,
|
| 712 |
+
"num_tokens": 1585718.0,
|
| 713 |
+
"step": 680
|
| 714 |
+
},
|
| 715 |
+
{
|
| 716 |
+
"epoch": 1.692403486924035,
|
| 717 |
+
"eval_entropy": 0.539117265406043,
|
| 718 |
+
"eval_loss": 0.53994220495224,
|
| 719 |
+
"eval_mean_token_accuracy": 0.8488582601380903,
|
| 720 |
+
"eval_num_tokens": 1585718.0,
|
| 721 |
+
"eval_runtime": 86.5296,
|
| 722 |
+
"eval_samples_per_second": 15.902,
|
| 723 |
+
"eval_steps_per_second": 1.988,
|
| 724 |
+
"step": 680
|
| 725 |
+
},
|
| 726 |
+
{
|
| 727 |
+
"entropy": 0.5543891470879316,
|
| 728 |
+
"epoch": 1.7422166874221667,
|
| 729 |
+
"grad_norm": 0.6068442463874817,
|
| 730 |
+
"learning_rate": 0.0001982204261804297,
|
| 731 |
+
"loss": 0.498047399520874,
|
| 732 |
+
"mean_token_accuracy": 0.8554679051041603,
|
| 733 |
+
"num_tokens": 1635718.0,
|
| 734 |
+
"step": 700
|
| 735 |
+
},
|
| 736 |
+
{
|
| 737 |
+
"epoch": 1.7422166874221667,
|
| 738 |
+
"eval_entropy": 0.5703774151760478,
|
| 739 |
+
"eval_loss": 0.5300245881080627,
|
| 740 |
+
"eval_mean_token_accuracy": 0.850798153946566,
|
| 741 |
+
"eval_num_tokens": 1635718.0,
|
| 742 |
+
"eval_runtime": 86.6456,
|
| 743 |
+
"eval_samples_per_second": 15.881,
|
| 744 |
+
"eval_steps_per_second": 1.985,
|
| 745 |
+
"step": 700
|
| 746 |
+
},
|
| 747 |
+
{
|
| 748 |
+
"entropy": 0.546524541825056,
|
| 749 |
+
"epoch": 1.792029887920299,
|
| 750 |
+
"grad_norm": 0.7274155020713806,
|
| 751 |
+
"learning_rate": 0.00019775939618332566,
|
| 752 |
+
"loss": 0.4988589286804199,
|
| 753 |
+
"mean_token_accuracy": 0.853422473371029,
|
| 754 |
+
"num_tokens": 1681291.0,
|
| 755 |
+
"step": 720
|
| 756 |
+
},
|
| 757 |
+
{
|
| 758 |
+
"epoch": 1.792029887920299,
|
| 759 |
+
"eval_entropy": 0.5614905688305234,
|
| 760 |
+
"eval_loss": 0.5350332260131836,
|
| 761 |
+
"eval_mean_token_accuracy": 0.8492204359797544,
|
| 762 |
+
"eval_num_tokens": 1681291.0,
|
| 763 |
+
"eval_runtime": 86.7581,
|
| 764 |
+
"eval_samples_per_second": 15.86,
|
| 765 |
+
"eval_steps_per_second": 1.983,
|
| 766 |
+
"step": 720
|
| 767 |
+
},
|
| 768 |
+
{
|
| 769 |
+
"entropy": 0.5519792139530182,
|
| 770 |
+
"epoch": 1.841843088418431,
|
| 771 |
+
"grad_norm": 0.663466215133667,
|
| 772 |
+
"learning_rate": 0.00019726911748712167,
|
| 773 |
+
"loss": 0.5099314212799072,
|
| 774 |
+
"mean_token_accuracy": 0.848412600159645,
|
| 775 |
+
"num_tokens": 1729102.0,
|
| 776 |
+
"step": 740
|
| 777 |
+
},
|
| 778 |
+
{
|
| 779 |
+
"epoch": 1.841843088418431,
|
| 780 |
+
"eval_entropy": 0.5583519090053647,
|
| 781 |
+
"eval_loss": 0.530483603477478,
|
| 782 |
+
"eval_mean_token_accuracy": 0.8500003374593202,
|
| 783 |
+
"eval_num_tokens": 1729102.0,
|
| 784 |
+
"eval_runtime": 86.3961,
|
| 785 |
+
"eval_samples_per_second": 15.927,
|
| 786 |
+
"eval_steps_per_second": 1.991,
|
| 787 |
+
"step": 740
|
| 788 |
+
},
|
| 789 |
+
{
|
| 790 |
+
"entropy": 0.5454779766499996,
|
| 791 |
+
"epoch": 1.891656288916563,
|
| 792 |
+
"grad_norm": 0.890394926071167,
|
| 793 |
+
"learning_rate": 0.00019674973795318548,
|
| 794 |
+
"loss": 0.4931994915008545,
|
| 795 |
+
"mean_token_accuracy": 0.8540832489728928,
|
| 796 |
+
"num_tokens": 1773578.0,
|
| 797 |
+
"step": 760
|
| 798 |
+
},
|
| 799 |
+
{
|
| 800 |
+
"epoch": 1.891656288916563,
|
| 801 |
+
"eval_entropy": 0.572755502406941,
|
| 802 |
+
"eval_loss": 0.5415747761726379,
|
| 803 |
+
"eval_mean_token_accuracy": 0.8444425803284312,
|
| 804 |
+
"eval_num_tokens": 1773578.0,
|
| 805 |
+
"eval_runtime": 86.4323,
|
| 806 |
+
"eval_samples_per_second": 15.92,
|
| 807 |
+
"eval_steps_per_second": 1.99,
|
| 808 |
+
"step": 760
|
| 809 |
+
},
|
| 810 |
+
{
|
| 811 |
+
"entropy": 0.5392089951783419,
|
| 812 |
+
"epoch": 1.9414694894146949,
|
| 813 |
+
"grad_norm": 0.632411777973175,
|
| 814 |
+
"learning_rate": 0.00019620141421930058,
|
| 815 |
+
"loss": 0.4957888603210449,
|
| 816 |
+
"mean_token_accuracy": 0.8549866065382957,
|
| 817 |
+
"num_tokens": 1821725.0,
|
| 818 |
+
"step": 780
|
| 819 |
+
},
|
| 820 |
+
{
|
| 821 |
+
"epoch": 1.9414694894146949,
|
| 822 |
+
"eval_entropy": 0.540764772961306,
|
| 823 |
+
"eval_loss": 0.5327216386795044,
|
| 824 |
+
"eval_mean_token_accuracy": 0.850631088364956,
|
| 825 |
+
"eval_num_tokens": 1821725.0,
|
| 826 |
+
"eval_runtime": 86.8097,
|
| 827 |
+
"eval_samples_per_second": 15.851,
|
| 828 |
+
"eval_steps_per_second": 1.981,
|
| 829 |
+
"step": 780
|
| 830 |
+
},
|
| 831 |
+
{
|
| 832 |
+
"entropy": 0.5674678739160299,
|
| 833 |
+
"epoch": 1.9912826899128269,
|
| 834 |
+
"grad_norm": 0.6958843469619751,
|
| 835 |
+
"learning_rate": 0.0001956243116524263,
|
| 836 |
+
"loss": 0.504389762878418,
|
| 837 |
+
"mean_token_accuracy": 0.8527948908507824,
|
| 838 |
+
"num_tokens": 1868431.0,
|
| 839 |
+
"step": 800
|
| 840 |
+
},
|
| 841 |
+
{
|
| 842 |
+
"epoch": 1.9912826899128269,
|
| 843 |
+
"eval_entropy": 0.530262403190136,
|
| 844 |
+
"eval_loss": 0.5308871865272522,
|
| 845 |
+
"eval_mean_token_accuracy": 0.8522498046242913,
|
| 846 |
+
"eval_num_tokens": 1868431.0,
|
| 847 |
+
"eval_runtime": 86.7942,
|
| 848 |
+
"eval_samples_per_second": 15.854,
|
| 849 |
+
"eval_steps_per_second": 1.982,
|
| 850 |
+
"step": 800
|
| 851 |
+
},
|
| 852 |
+
{
|
| 853 |
+
"entropy": 0.4742849511213792,
|
| 854 |
+
"epoch": 2.0398505603985058,
|
| 855 |
+
"grad_norm": 0.6941492557525635,
|
| 856 |
+
"learning_rate": 0.00019501860429882556,
|
| 857 |
+
"loss": 0.418599271774292,
|
| 858 |
+
"mean_token_accuracy": 0.8748210859604371,
|
| 859 |
+
"num_tokens": 1915280.0,
|
| 860 |
+
"step": 820
|
| 861 |
+
},
|
| 862 |
+
{
|
| 863 |
+
"epoch": 2.0398505603985058,
|
| 864 |
+
"eval_entropy": 0.504602165069691,
|
| 865 |
+
"eval_loss": 0.542878270149231,
|
| 866 |
+
"eval_mean_token_accuracy": 0.8507604484641275,
|
| 867 |
+
"eval_num_tokens": 1915280.0,
|
| 868 |
+
"eval_runtime": 86.7841,
|
| 869 |
+
"eval_samples_per_second": 15.855,
|
| 870 |
+
"eval_steps_per_second": 1.982,
|
| 871 |
+
"step": 820
|
| 872 |
+
},
|
| 873 |
+
{
|
| 874 |
+
"entropy": 0.45857742577791216,
|
| 875 |
+
"epoch": 2.0896637608966375,
|
| 876 |
+
"grad_norm": 0.5791997909545898,
|
| 877 |
+
"learning_rate": 0.00019438447483157478,
|
| 878 |
+
"loss": 0.399777889251709,
|
| 879 |
+
"mean_token_accuracy": 0.8754058346152306,
|
| 880 |
+
"num_tokens": 1965306.0,
|
| 881 |
+
"step": 840
|
| 882 |
+
},
|
| 883 |
+
{
|
| 884 |
+
"epoch": 2.0896637608966375,
|
| 885 |
+
"eval_entropy": 0.5028848362176918,
|
| 886 |
+
"eval_loss": 0.5356478095054626,
|
| 887 |
+
"eval_mean_token_accuracy": 0.8525635412959165,
|
| 888 |
+
"eval_num_tokens": 1965306.0,
|
| 889 |
+
"eval_runtime": 86.6707,
|
| 890 |
+
"eval_samples_per_second": 15.876,
|
| 891 |
+
"eval_steps_per_second": 1.985,
|
| 892 |
+
"step": 840
|
| 893 |
+
},
|
| 894 |
+
{
|
| 895 |
+
"entropy": 0.4869446292519569,
|
| 896 |
+
"epoch": 2.1394769613947697,
|
| 897 |
+
"grad_norm": 0.6483516693115234,
|
| 898 |
+
"learning_rate": 0.00019372211449547223,
|
| 899 |
+
"loss": 0.40715818405151366,
|
| 900 |
+
"mean_token_accuracy": 0.875113020837307,
|
| 901 |
+
"num_tokens": 2008562.0,
|
| 902 |
+
"step": 860
|
| 903 |
+
},
|
| 904 |
+
{
|
| 905 |
+
"epoch": 2.1394769613947697,
|
| 906 |
+
"eval_entropy": 0.4928991326759028,
|
| 907 |
+
"eval_loss": 0.5419561862945557,
|
| 908 |
+
"eval_mean_token_accuracy": 0.8516040146350861,
|
| 909 |
+
"eval_num_tokens": 2008562.0,
|
| 910 |
+
"eval_runtime": 87.0686,
|
| 911 |
+
"eval_samples_per_second": 15.804,
|
| 912 |
+
"eval_steps_per_second": 1.975,
|
| 913 |
+
"step": 860
|
| 914 |
+
},
|
| 915 |
+
{
|
| 916 |
+
"entropy": 0.45819590501487256,
|
| 917 |
+
"epoch": 2.1892901618929015,
|
| 918 |
+
"grad_norm": 0.6661920547485352,
|
| 919 |
+
"learning_rate": 0.00019303172304936108,
|
| 920 |
+
"loss": 0.39511430263519287,
|
| 921 |
+
"mean_token_accuracy": 0.8780680045485496,
|
| 922 |
+
"num_tokens": 2056474.0,
|
| 923 |
+
"step": 880
|
| 924 |
+
},
|
| 925 |
+
{
|
| 926 |
+
"epoch": 2.1892901618929015,
|
| 927 |
+
"eval_entropy": 0.48602560647698334,
|
| 928 |
+
"eval_loss": 0.5436084866523743,
|
| 929 |
+
"eval_mean_token_accuracy": 0.8500938470973525,
|
| 930 |
+
"eval_num_tokens": 2056474.0,
|
| 931 |
+
"eval_runtime": 86.6809,
|
| 932 |
+
"eval_samples_per_second": 15.874,
|
| 933 |
+
"eval_steps_per_second": 1.984,
|
| 934 |
+
"step": 880
|
| 935 |
+
},
|
| 936 |
+
{
|
| 937 |
+
"entropy": 0.4780638810247183,
|
| 938 |
+
"epoch": 2.2391033623910337,
|
| 939 |
+
"grad_norm": 0.6870484352111816,
|
| 940 |
+
"learning_rate": 0.0001923135087058851,
|
| 941 |
+
"loss": 0.4061615467071533,
|
| 942 |
+
"mean_token_accuracy": 0.8766494184732437,
|
| 943 |
+
"num_tokens": 2103543.0,
|
| 944 |
+
"step": 900
|
| 945 |
+
},
|
| 946 |
+
{
|
| 947 |
+
"epoch": 2.2391033623910337,
|
| 948 |
+
"eval_entropy": 0.48236206035281337,
|
| 949 |
+
"eval_loss": 0.5446090698242188,
|
| 950 |
+
"eval_mean_token_accuracy": 0.8507725513258646,
|
| 951 |
+
"eval_num_tokens": 2103543.0,
|
| 952 |
+
"eval_runtime": 86.7398,
|
| 953 |
+
"eval_samples_per_second": 15.864,
|
| 954 |
+
"eval_steps_per_second": 1.983,
|
| 955 |
+
"step": 900
|
| 956 |
+
},
|
| 957 |
+
{
|
| 958 |
+
"entropy": 0.463029869645834,
|
| 959 |
+
"epoch": 2.2889165628891655,
|
| 960 |
+
"grad_norm": 0.6894590854644775,
|
| 961 |
+
"learning_rate": 0.00019156768806869427,
|
| 962 |
+
"loss": 0.39602413177490237,
|
| 963 |
+
"mean_token_accuracy": 0.876420046389103,
|
| 964 |
+
"num_tokens": 2147861.0,
|
| 965 |
+
"step": 920
|
| 966 |
+
},
|
| 967 |
+
{
|
| 968 |
+
"epoch": 2.2889165628891655,
|
| 969 |
+
"eval_entropy": 0.4904779093556626,
|
| 970 |
+
"eval_loss": 0.5404934287071228,
|
| 971 |
+
"eval_mean_token_accuracy": 0.852238280828609,
|
| 972 |
+
"eval_num_tokens": 2147861.0,
|
| 973 |
+
"eval_runtime": 86.5348,
|
| 974 |
+
"eval_samples_per_second": 15.901,
|
| 975 |
+
"eval_steps_per_second": 1.988,
|
| 976 |
+
"step": 920
|
| 977 |
+
},
|
| 978 |
+
{
|
| 979 |
+
"entropy": 0.4817025110125542,
|
| 980 |
+
"epoch": 2.3387297633872977,
|
| 981 |
+
"grad_norm": 0.7756227254867554,
|
| 982 |
+
"learning_rate": 0.00019079448606712033,
|
| 983 |
+
"loss": 0.4177968502044678,
|
| 984 |
+
"mean_token_accuracy": 0.8712256088852882,
|
| 985 |
+
"num_tokens": 2190561.0,
|
| 986 |
+
"step": 940
|
| 987 |
+
},
|
| 988 |
+
{
|
| 989 |
+
"epoch": 2.3387297633872977,
|
| 990 |
+
"eval_entropy": 0.5153802815218305,
|
| 991 |
+
"eval_loss": 0.5424937605857849,
|
| 992 |
+
"eval_mean_token_accuracy": 0.8506565759348315,
|
| 993 |
+
"eval_num_tokens": 2190561.0,
|
| 994 |
+
"eval_runtime": 86.8973,
|
| 995 |
+
"eval_samples_per_second": 15.835,
|
| 996 |
+
"eval_steps_per_second": 1.979,
|
| 997 |
+
"step": 940
|
| 998 |
+
},
|
| 999 |
+
{
|
| 1000 |
+
"entropy": 0.46456389091908934,
|
| 1001 |
+
"epoch": 2.3885429638854294,
|
| 1002 |
+
"grad_norm": 1.2000319957733154,
|
| 1003 |
+
"learning_rate": 0.00018999413588834105,
|
| 1004 |
+
"loss": 0.4084665775299072,
|
| 1005 |
+
"mean_token_accuracy": 0.8750658087432385,
|
| 1006 |
+
"num_tokens": 2239412.0,
|
| 1007 |
+
"step": 960
|
| 1008 |
+
},
|
| 1009 |
+
{
|
| 1010 |
+
"epoch": 2.3885429638854294,
|
| 1011 |
+
"eval_entropy": 0.4849439303195754,
|
| 1012 |
+
"eval_loss": 0.545662522315979,
|
| 1013 |
+
"eval_mean_token_accuracy": 0.8491013112456299,
|
| 1014 |
+
"eval_num_tokens": 2239412.0,
|
| 1015 |
+
"eval_runtime": 86.9049,
|
| 1016 |
+
"eval_samples_per_second": 15.833,
|
| 1017 |
+
"eval_steps_per_second": 1.979,
|
| 1018 |
+
"step": 960
|
| 1019 |
+
},
|
| 1020 |
+
{
|
| 1021 |
+
"entropy": 0.4857471022754908,
|
| 1022 |
+
"epoch": 2.4383561643835616,
|
| 1023 |
+
"grad_norm": 0.9696341753005981,
|
| 1024 |
+
"learning_rate": 0.0001891668789070541,
|
| 1025 |
+
"loss": 0.4149796962738037,
|
| 1026 |
+
"mean_token_accuracy": 0.8704176343977451,
|
| 1027 |
+
"num_tokens": 2286283.0,
|
| 1028 |
+
"step": 980
|
| 1029 |
+
},
|
| 1030 |
+
{
|
| 1031 |
+
"epoch": 2.4383561643835616,
|
| 1032 |
+
"eval_entropy": 0.4872790058684904,
|
| 1033 |
+
"eval_loss": 0.5412707924842834,
|
| 1034 |
+
"eval_mean_token_accuracy": 0.8509329602468846,
|
| 1035 |
+
"eval_num_tokens": 2286283.0,
|
| 1036 |
+
"eval_runtime": 86.7846,
|
| 1037 |
+
"eval_samples_per_second": 15.855,
|
| 1038 |
+
"eval_steps_per_second": 1.982,
|
| 1039 |
+
"step": 980
|
| 1040 |
+
},
|
| 1041 |
+
{
|
| 1042 |
+
"entropy": 0.4727417893707752,
|
| 1043 |
+
"epoch": 2.488169364881694,
|
| 1044 |
+
"grad_norm": 0.7852500677108765,
|
| 1045 |
+
"learning_rate": 0.0001883129646126818,
|
| 1046 |
+
"loss": 0.4142886161804199,
|
| 1047 |
+
"mean_token_accuracy": 0.8712429471313954,
|
| 1048 |
+
"num_tokens": 2333733.0,
|
| 1049 |
+
"step": 1000
|
| 1050 |
+
},
|
| 1051 |
+
{
|
| 1052 |
+
"epoch": 2.488169364881694,
|
| 1053 |
+
"eval_entropy": 0.5386548059624295,
|
| 1054 |
+
"eval_loss": 0.536101222038269,
|
| 1055 |
+
"eval_mean_token_accuracy": 0.8499491239009902,
|
| 1056 |
+
"eval_num_tokens": 2333733.0,
|
| 1057 |
+
"eval_runtime": 86.9501,
|
| 1058 |
+
"eval_samples_per_second": 15.825,
|
| 1059 |
+
"eval_steps_per_second": 1.978,
|
| 1060 |
+
"step": 1000
|
| 1061 |
+
},
|
| 1062 |
+
{
|
| 1063 |
+
"entropy": 0.4673406321555376,
|
| 1064 |
+
"epoch": 2.5379825653798256,
|
| 1065 |
+
"grad_norm": 0.7133921384811401,
|
| 1066 |
+
"learning_rate": 0.0001874326505341286,
|
| 1067 |
+
"loss": 0.40857529640197754,
|
| 1068 |
+
"mean_token_accuracy": 0.8747925907373428,
|
| 1069 |
+
"num_tokens": 2384270.0,
|
| 1070 |
+
"step": 1020
|
| 1071 |
+
},
|
| 1072 |
+
{
|
| 1073 |
+
"epoch": 2.5379825653798256,
|
| 1074 |
+
"eval_entropy": 0.495788364909416,
|
| 1075 |
+
"eval_loss": 0.5418923497200012,
|
| 1076 |
+
"eval_mean_token_accuracy": 0.851321972040243,
|
| 1077 |
+
"eval_num_tokens": 2384270.0,
|
| 1078 |
+
"eval_runtime": 86.7154,
|
| 1079 |
+
"eval_samples_per_second": 15.868,
|
| 1080 |
+
"eval_steps_per_second": 1.983,
|
| 1081 |
+
"step": 1020
|
| 1082 |
+
},
|
| 1083 |
+
{
|
| 1084 |
+
"entropy": 0.47599745728075504,
|
| 1085 |
+
"epoch": 2.587795765877958,
|
| 1086 |
+
"grad_norm": 0.8202953338623047,
|
| 1087 |
+
"learning_rate": 0.0001865262021621137,
|
| 1088 |
+
"loss": 0.40998234748840334,
|
| 1089 |
+
"mean_token_accuracy": 0.8758242674171924,
|
| 1090 |
+
"num_tokens": 2428036.0,
|
| 1091 |
+
"step": 1040
|
| 1092 |
+
},
|
| 1093 |
+
{
|
| 1094 |
+
"epoch": 2.587795765877958,
|
| 1095 |
+
"eval_entropy": 0.4887966953737791,
|
| 1096 |
+
"eval_loss": 0.5408804416656494,
|
| 1097 |
+
"eval_mean_token_accuracy": 0.8512661065473113,
|
| 1098 |
+
"eval_num_tokens": 2428036.0,
|
| 1099 |
+
"eval_runtime": 86.7869,
|
| 1100 |
+
"eval_samples_per_second": 15.855,
|
| 1101 |
+
"eval_steps_per_second": 1.982,
|
| 1102 |
+
"step": 1040
|
| 1103 |
+
},
|
| 1104 |
+
{
|
| 1105 |
+
"entropy": 0.4824396539479494,
|
| 1106 |
+
"epoch": 2.6376089663760895,
|
| 1107 |
+
"grad_norm": 0.6507360935211182,
|
| 1108 |
+
"learning_rate": 0.00018559389286910275,
|
| 1109 |
+
"loss": 0.4165764808654785,
|
| 1110 |
+
"mean_token_accuracy": 0.8722914069890976,
|
| 1111 |
+
"num_tokens": 2476815.0,
|
| 1112 |
+
"step": 1060
|
| 1113 |
+
},
|
| 1114 |
+
{
|
| 1115 |
+
"epoch": 2.6376089663760895,
|
| 1116 |
+
"eval_entropy": 0.4793398808254752,
|
| 1117 |
+
"eval_loss": 0.5326959490776062,
|
| 1118 |
+
"eval_mean_token_accuracy": 0.8534493650807891,
|
| 1119 |
+
"eval_num_tokens": 2476815.0,
|
| 1120 |
+
"eval_runtime": 86.9559,
|
| 1121 |
+
"eval_samples_per_second": 15.824,
|
| 1122 |
+
"eval_steps_per_second": 1.978,
|
| 1123 |
+
"step": 1060
|
| 1124 |
+
},
|
| 1125 |
+
{
|
| 1126 |
+
"entropy": 0.4605010639876127,
|
| 1127 |
+
"epoch": 2.6874221668742218,
|
| 1128 |
+
"grad_norm": 0.6740535497665405,
|
| 1129 |
+
"learning_rate": 0.00018463600382686253,
|
| 1130 |
+
"loss": 0.4123940944671631,
|
| 1131 |
+
"mean_token_accuracy": 0.8733638986945153,
|
| 1132 |
+
"num_tokens": 2527131.0,
|
| 1133 |
+
"step": 1080
|
| 1134 |
+
},
|
| 1135 |
+
{
|
| 1136 |
+
"epoch": 2.6874221668742218,
|
| 1137 |
+
"eval_entropy": 0.47902208583992584,
|
| 1138 |
+
"eval_loss": 0.5372340083122253,
|
| 1139 |
+
"eval_mean_token_accuracy": 0.851325950303743,
|
| 1140 |
+
"eval_num_tokens": 2527131.0,
|
| 1141 |
+
"eval_runtime": 86.9638,
|
| 1142 |
+
"eval_samples_per_second": 15.823,
|
| 1143 |
+
"eval_steps_per_second": 1.978,
|
| 1144 |
+
"step": 1080
|
| 1145 |
+
},
|
| 1146 |
+
{
|
| 1147 |
+
"entropy": 0.4872019402682781,
|
| 1148 |
+
"epoch": 2.7372353673723535,
|
| 1149 |
+
"grad_norm": 0.6994742155075073,
|
| 1150 |
+
"learning_rate": 0.0001836528239216632,
|
| 1151 |
+
"loss": 0.41599602699279786,
|
| 1152 |
+
"mean_token_accuracy": 0.872775862365961,
|
| 1153 |
+
"num_tokens": 2572537.0,
|
| 1154 |
+
"step": 1100
|
| 1155 |
+
},
|
| 1156 |
+
{
|
| 1157 |
+
"epoch": 2.7372353673723535,
|
| 1158 |
+
"eval_entropy": 0.4893243626453156,
|
| 1159 |
+
"eval_loss": 0.5327795743942261,
|
| 1160 |
+
"eval_mean_token_accuracy": 0.8537560302850812,
|
| 1161 |
+
"eval_num_tokens": 2572537.0,
|
| 1162 |
+
"eval_runtime": 86.823,
|
| 1163 |
+
"eval_samples_per_second": 15.848,
|
| 1164 |
+
"eval_steps_per_second": 1.981,
|
| 1165 |
+
"step": 1100
|
| 1166 |
+
}
|
| 1167 |
+
],
|
| 1168 |
+
"logging_steps": 20,
|
| 1169 |
+
"max_steps": 4020,
|
| 1170 |
+
"num_input_tokens_seen": 0,
|
| 1171 |
+
"num_train_epochs": 10,
|
| 1172 |
+
"save_steps": 20,
|
| 1173 |
+
"stateful_callbacks": {
|
| 1174 |
+
"TrainerControl": {
|
| 1175 |
+
"args": {
|
| 1176 |
+
"should_epoch_stop": false,
|
| 1177 |
+
"should_evaluate": false,
|
| 1178 |
+
"should_log": false,
|
| 1179 |
+
"should_save": true,
|
| 1180 |
+
"should_training_stop": false
|
| 1181 |
+
},
|
| 1182 |
+
"attributes": {}
|
| 1183 |
+
}
|
| 1184 |
+
},
|
| 1185 |
+
"total_flos": 1.0877774590688256e+17,
|
| 1186 |
+
"train_batch_size": 4,
|
| 1187 |
+
"trial_name": null,
|
| 1188 |
+
"trial_params": null
|
| 1189 |
+
}
|
overgeneralisation_original_Swedish/Qwen3.5-4B-Base_overgeneralisation_splits_original_features_train_overgeneralisation_splits_original_features_test1/checkpoint-1120/README.md
ADDED
|
@@ -0,0 +1,209 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
---
|
| 2 |
+
base_model: Qwen/Qwen3.5-4B-Base
|
| 3 |
+
library_name: peft
|
| 4 |
+
pipeline_tag: text-generation
|
| 5 |
+
tags:
|
| 6 |
+
- base_model:adapter:Qwen/Qwen3.5-4B-Base
|
| 7 |
+
- lora
|
| 8 |
+
- sft
|
| 9 |
+
- transformers
|
| 10 |
+
- trl
|
| 11 |
+
---
|
| 12 |
+
|
| 13 |
+
# Model Card for Model ID
|
| 14 |
+
|
| 15 |
+
<!-- Provide a quick summary of what the model is/does. -->
|
| 16 |
+
|
| 17 |
+
|
| 18 |
+
|
| 19 |
+
## Model Details
|
| 20 |
+
|
| 21 |
+
### Model Description
|
| 22 |
+
|
| 23 |
+
<!-- Provide a longer summary of what this model is. -->
|
| 24 |
+
|
| 25 |
+
|
| 26 |
+
|
| 27 |
+
- **Developed by:** [More Information Needed]
|
| 28 |
+
- **Funded by [optional]:** [More Information Needed]
|
| 29 |
+
- **Shared by [optional]:** [More Information Needed]
|
| 30 |
+
- **Model type:** [More Information Needed]
|
| 31 |
+
- **Language(s) (NLP):** [More Information Needed]
|
| 32 |
+
- **License:** [More Information Needed]
|
| 33 |
+
- **Finetuned from model [optional]:** [More Information Needed]
|
| 34 |
+
|
| 35 |
+
### Model Sources [optional]
|
| 36 |
+
|
| 37 |
+
<!-- Provide the basic links for the model. -->
|
| 38 |
+
|
| 39 |
+
- **Repository:** [More Information Needed]
|
| 40 |
+
- **Paper [optional]:** [More Information Needed]
|
| 41 |
+
- **Demo [optional]:** [More Information Needed]
|
| 42 |
+
|
| 43 |
+
## Uses
|
| 44 |
+
|
| 45 |
+
<!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
|
| 46 |
+
|
| 47 |
+
### Direct Use
|
| 48 |
+
|
| 49 |
+
<!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
|
| 50 |
+
|
| 51 |
+
[More Information Needed]
|
| 52 |
+
|
| 53 |
+
### Downstream Use [optional]
|
| 54 |
+
|
| 55 |
+
<!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
|
| 56 |
+
|
| 57 |
+
[More Information Needed]
|
| 58 |
+
|
| 59 |
+
### Out-of-Scope Use
|
| 60 |
+
|
| 61 |
+
<!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
|
| 62 |
+
|
| 63 |
+
[More Information Needed]
|
| 64 |
+
|
| 65 |
+
## Bias, Risks, and Limitations
|
| 66 |
+
|
| 67 |
+
<!-- This section is meant to convey both technical and sociotechnical limitations. -->
|
| 68 |
+
|
| 69 |
+
[More Information Needed]
|
| 70 |
+
|
| 71 |
+
### Recommendations
|
| 72 |
+
|
| 73 |
+
<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
|
| 74 |
+
|
| 75 |
+
Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
|
| 76 |
+
|
| 77 |
+
## How to Get Started with the Model
|
| 78 |
+
|
| 79 |
+
Use the code below to get started with the model.
|
| 80 |
+
|
| 81 |
+
[More Information Needed]
|
| 82 |
+
|
| 83 |
+
## Training Details
|
| 84 |
+
|
| 85 |
+
### Training Data
|
| 86 |
+
|
| 87 |
+
<!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
|
| 88 |
+
|
| 89 |
+
[More Information Needed]
|
| 90 |
+
|
| 91 |
+
### Training Procedure
|
| 92 |
+
|
| 93 |
+
<!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
|
| 94 |
+
|
| 95 |
+
#### Preprocessing [optional]
|
| 96 |
+
|
| 97 |
+
[More Information Needed]
|
| 98 |
+
|
| 99 |
+
|
| 100 |
+
#### Training Hyperparameters
|
| 101 |
+
|
| 102 |
+
- **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
|
| 103 |
+
|
| 104 |
+
#### Speeds, Sizes, Times [optional]
|
| 105 |
+
|
| 106 |
+
<!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
|
| 107 |
+
|
| 108 |
+
[More Information Needed]
|
| 109 |
+
|
| 110 |
+
## Evaluation
|
| 111 |
+
|
| 112 |
+
<!-- This section describes the evaluation protocols and provides the results. -->
|
| 113 |
+
|
| 114 |
+
### Testing Data, Factors & Metrics
|
| 115 |
+
|
| 116 |
+
#### Testing Data
|
| 117 |
+
|
| 118 |
+
<!-- This should link to a Dataset Card if possible. -->
|
| 119 |
+
|
| 120 |
+
[More Information Needed]
|
| 121 |
+
|
| 122 |
+
#### Factors
|
| 123 |
+
|
| 124 |
+
<!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
|
| 125 |
+
|
| 126 |
+
[More Information Needed]
|
| 127 |
+
|
| 128 |
+
#### Metrics
|
| 129 |
+
|
| 130 |
+
<!-- These are the evaluation metrics being used, ideally with a description of why. -->
|
| 131 |
+
|
| 132 |
+
[More Information Needed]
|
| 133 |
+
|
| 134 |
+
### Results
|
| 135 |
+
|
| 136 |
+
[More Information Needed]
|
| 137 |
+
|
| 138 |
+
#### Summary
|
| 139 |
+
|
| 140 |
+
|
| 141 |
+
|
| 142 |
+
## Model Examination [optional]
|
| 143 |
+
|
| 144 |
+
<!-- Relevant interpretability work for the model goes here -->
|
| 145 |
+
|
| 146 |
+
[More Information Needed]
|
| 147 |
+
|
| 148 |
+
## Environmental Impact
|
| 149 |
+
|
| 150 |
+
<!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
|
| 151 |
+
|
| 152 |
+
Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
|
| 153 |
+
|
| 154 |
+
- **Hardware Type:** [More Information Needed]
|
| 155 |
+
- **Hours used:** [More Information Needed]
|
| 156 |
+
- **Cloud Provider:** [More Information Needed]
|
| 157 |
+
- **Compute Region:** [More Information Needed]
|
| 158 |
+
- **Carbon Emitted:** [More Information Needed]
|
| 159 |
+
|
| 160 |
+
## Technical Specifications [optional]
|
| 161 |
+
|
| 162 |
+
### Model Architecture and Objective
|
| 163 |
+
|
| 164 |
+
[More Information Needed]
|
| 165 |
+
|
| 166 |
+
### Compute Infrastructure
|
| 167 |
+
|
| 168 |
+
[More Information Needed]
|
| 169 |
+
|
| 170 |
+
#### Hardware
|
| 171 |
+
|
| 172 |
+
[More Information Needed]
|
| 173 |
+
|
| 174 |
+
#### Software
|
| 175 |
+
|
| 176 |
+
[More Information Needed]
|
| 177 |
+
|
| 178 |
+
## Citation [optional]
|
| 179 |
+
|
| 180 |
+
<!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
|
| 181 |
+
|
| 182 |
+
**BibTeX:**
|
| 183 |
+
|
| 184 |
+
[More Information Needed]
|
| 185 |
+
|
| 186 |
+
**APA:**
|
| 187 |
+
|
| 188 |
+
[More Information Needed]
|
| 189 |
+
|
| 190 |
+
## Glossary [optional]
|
| 191 |
+
|
| 192 |
+
<!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
|
| 193 |
+
|
| 194 |
+
[More Information Needed]
|
| 195 |
+
|
| 196 |
+
## More Information [optional]
|
| 197 |
+
|
| 198 |
+
[More Information Needed]
|
| 199 |
+
|
| 200 |
+
## Model Card Authors [optional]
|
| 201 |
+
|
| 202 |
+
[More Information Needed]
|
| 203 |
+
|
| 204 |
+
## Model Card Contact
|
| 205 |
+
|
| 206 |
+
[More Information Needed]
|
| 207 |
+
### Framework versions
|
| 208 |
+
|
| 209 |
+
- PEFT 0.18.1
|
overgeneralisation_original_Swedish/Qwen3.5-4B-Base_overgeneralisation_splits_original_features_train_overgeneralisation_splits_original_features_test1/checkpoint-1120/adapter_config.json
ADDED
|
@@ -0,0 +1,46 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
{
|
| 2 |
+
"alora_invocation_tokens": null,
|
| 3 |
+
"alpha_pattern": {},
|
| 4 |
+
"arrow_config": null,
|
| 5 |
+
"auto_mapping": null,
|
| 6 |
+
"base_model_name_or_path": "Qwen/Qwen3.5-4B-Base",
|
| 7 |
+
"bias": "none",
|
| 8 |
+
"corda_config": null,
|
| 9 |
+
"ensure_weight_tying": false,
|
| 10 |
+
"eva_config": null,
|
| 11 |
+
"exclude_modules": null,
|
| 12 |
+
"fan_in_fan_out": false,
|
| 13 |
+
"inference_mode": true,
|
| 14 |
+
"init_lora_weights": true,
|
| 15 |
+
"layer_replication": null,
|
| 16 |
+
"layers_pattern": null,
|
| 17 |
+
"layers_to_transform": null,
|
| 18 |
+
"loftq_config": {},
|
| 19 |
+
"lora_alpha": 256,
|
| 20 |
+
"lora_bias": false,
|
| 21 |
+
"lora_dropout": 0.0005183818805460705,
|
| 22 |
+
"megatron_config": null,
|
| 23 |
+
"megatron_core": "megatron.core",
|
| 24 |
+
"modules_to_save": null,
|
| 25 |
+
"peft_type": "LORA",
|
| 26 |
+
"peft_version": "0.18.1",
|
| 27 |
+
"qalora_group_size": 16,
|
| 28 |
+
"r": 128,
|
| 29 |
+
"rank_pattern": {},
|
| 30 |
+
"revision": null,
|
| 31 |
+
"target_modules": [
|
| 32 |
+
"up_proj",
|
| 33 |
+
"q_proj",
|
| 34 |
+
"o_proj",
|
| 35 |
+
"v_proj",
|
| 36 |
+
"k_proj",
|
| 37 |
+
"gate_proj",
|
| 38 |
+
"down_proj"
|
| 39 |
+
],
|
| 40 |
+
"target_parameters": null,
|
| 41 |
+
"task_type": "CAUSAL_LM",
|
| 42 |
+
"trainable_token_indices": null,
|
| 43 |
+
"use_dora": false,
|
| 44 |
+
"use_qalora": false,
|
| 45 |
+
"use_rslora": false
|
| 46 |
+
}
|
overgeneralisation_original_Swedish/Qwen3.5-4B-Base_overgeneralisation_splits_original_features_train_overgeneralisation_splits_original_features_test1/checkpoint-1120/chat_template.jinja
ADDED
|
@@ -0,0 +1,154 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
{%- set image_count = namespace(value=0) %}
|
| 2 |
+
{%- set video_count = namespace(value=0) %}
|
| 3 |
+
{%- macro render_content(content, do_vision_count, is_system_content=false) %}
|
| 4 |
+
{%- if content is string %}
|
| 5 |
+
{{- content }}
|
| 6 |
+
{%- elif content is iterable and content is not mapping %}
|
| 7 |
+
{%- for item in content %}
|
| 8 |
+
{%- if 'image' in item or 'image_url' in item or item.type == 'image' %}
|
| 9 |
+
{%- if is_system_content %}
|
| 10 |
+
{{- raise_exception('System message cannot contain images.') }}
|
| 11 |
+
{%- endif %}
|
| 12 |
+
{%- if do_vision_count %}
|
| 13 |
+
{%- set image_count.value = image_count.value + 1 %}
|
| 14 |
+
{%- endif %}
|
| 15 |
+
{%- if add_vision_id %}
|
| 16 |
+
{{- 'Picture ' ~ image_count.value ~ ': ' }}
|
| 17 |
+
{%- endif %}
|
| 18 |
+
{{- '<|vision_start|><|image_pad|><|vision_end|>' }}
|
| 19 |
+
{%- elif 'video' in item or item.type == 'video' %}
|
| 20 |
+
{%- if is_system_content %}
|
| 21 |
+
{{- raise_exception('System message cannot contain videos.') }}
|
| 22 |
+
{%- endif %}
|
| 23 |
+
{%- if do_vision_count %}
|
| 24 |
+
{%- set video_count.value = video_count.value + 1 %}
|
| 25 |
+
{%- endif %}
|
| 26 |
+
{%- if add_vision_id %}
|
| 27 |
+
{{- 'Video ' ~ video_count.value ~ ': ' }}
|
| 28 |
+
{%- endif %}
|
| 29 |
+
{{- '<|vision_start|><|video_pad|><|vision_end|>' }}
|
| 30 |
+
{%- elif 'text' in item %}
|
| 31 |
+
{{- item.text }}
|
| 32 |
+
{%- else %}
|
| 33 |
+
{{- raise_exception('Unexpected item type in content.') }}
|
| 34 |
+
{%- endif %}
|
| 35 |
+
{%- endfor %}
|
| 36 |
+
{%- elif content is none or content is undefined %}
|
| 37 |
+
{{- '' }}
|
| 38 |
+
{%- else %}
|
| 39 |
+
{{- raise_exception('Unexpected content type.') }}
|
| 40 |
+
{%- endif %}
|
| 41 |
+
{%- endmacro %}
|
| 42 |
+
{%- if not messages %}
|
| 43 |
+
{{- raise_exception('No messages provided.') }}
|
| 44 |
+
{%- endif %}
|
| 45 |
+
{%- if tools and tools is iterable and tools is not mapping %}
|
| 46 |
+
{{- '<|im_start|>system\n' }}
|
| 47 |
+
{{- "# Tools\n\nYou have access to the following functions:\n\n<tools>" }}
|
| 48 |
+
{%- for tool in tools %}
|
| 49 |
+
{{- "\n" }}
|
| 50 |
+
{{- tool | tojson }}
|
| 51 |
+
{%- endfor %}
|
| 52 |
+
{{- "\n</tools>" }}
|
| 53 |
+
{{- '\n\nIf you choose to call a function ONLY reply in the following format with NO suffix:\n\n<tool_call>\n<function=example_function_name>\n<parameter=example_parameter_1>\nvalue_1\n</parameter>\n<parameter=example_parameter_2>\nThis is the value for the second parameter\nthat can span\nmultiple lines\n</parameter>\n</function>\n</tool_call>\n\n<IMPORTANT>\nReminder:\n- Function calls MUST follow the specified format: an inner <function=...></function> block must be nested within <tool_call></tool_call> XML tags\n- Required parameters MUST be specified\n- You may provide optional reasoning for your function call in natural language BEFORE the function call, but NOT after\n- If there is no function call available, answer the question like normal with your current knowledge and do not tell the user about function calls\n</IMPORTANT>' }}
|
| 54 |
+
{%- if messages[0].role == 'system' %}
|
| 55 |
+
{%- set content = render_content(messages[0].content, false, true)|trim %}
|
| 56 |
+
{%- if content %}
|
| 57 |
+
{{- '\n\n' + content }}
|
| 58 |
+
{%- endif %}
|
| 59 |
+
{%- endif %}
|
| 60 |
+
{{- '<|im_end|>\n' }}
|
| 61 |
+
{%- else %}
|
| 62 |
+
{%- if messages[0].role == 'system' %}
|
| 63 |
+
{%- set content = render_content(messages[0].content, false, true)|trim %}
|
| 64 |
+
{{- '<|im_start|>system\n' + content + '<|im_end|>\n' }}
|
| 65 |
+
{%- endif %}
|
| 66 |
+
{%- endif %}
|
| 67 |
+
{%- set ns = namespace(multi_step_tool=true, last_query_index=messages|length - 1) %}
|
| 68 |
+
{%- for message in messages[::-1] %}
|
| 69 |
+
{%- set index = (messages|length - 1) - loop.index0 %}
|
| 70 |
+
{%- if ns.multi_step_tool and message.role == "user" %}
|
| 71 |
+
{%- set content = render_content(message.content, false)|trim %}
|
| 72 |
+
{%- if not(content.startswith('<tool_response>') and content.endswith('</tool_response>')) %}
|
| 73 |
+
{%- set ns.multi_step_tool = false %}
|
| 74 |
+
{%- set ns.last_query_index = index %}
|
| 75 |
+
{%- endif %}
|
| 76 |
+
{%- endif %}
|
| 77 |
+
{%- endfor %}
|
| 78 |
+
{%- if ns.multi_step_tool %}
|
| 79 |
+
{{- raise_exception('No user query found in messages.') }}
|
| 80 |
+
{%- endif %}
|
| 81 |
+
{%- for message in messages %}
|
| 82 |
+
{%- set content = render_content(message.content, true)|trim %}
|
| 83 |
+
{%- if message.role == "system" %}
|
| 84 |
+
{%- if not loop.first %}
|
| 85 |
+
{{- raise_exception('System message must be at the beginning.') }}
|
| 86 |
+
{%- endif %}
|
| 87 |
+
{%- elif message.role == "user" %}
|
| 88 |
+
{{- '<|im_start|>' + message.role + '\n' + content + '<|im_end|>' + '\n' }}
|
| 89 |
+
{%- elif message.role == "assistant" %}
|
| 90 |
+
{%- set reasoning_content = '' %}
|
| 91 |
+
{%- if message.reasoning_content is string %}
|
| 92 |
+
{%- set reasoning_content = message.reasoning_content %}
|
| 93 |
+
{%- else %}
|
| 94 |
+
{%- if '</think>' in content %}
|
| 95 |
+
{%- set reasoning_content = content.split('</think>')[0].rstrip('\n').split('<think>')[-1].lstrip('\n') %}
|
| 96 |
+
{%- set content = content.split('</think>')[-1].lstrip('\n') %}
|
| 97 |
+
{%- endif %}
|
| 98 |
+
{%- endif %}
|
| 99 |
+
{%- set reasoning_content = reasoning_content|trim %}
|
| 100 |
+
{%- if loop.index0 > ns.last_query_index %}
|
| 101 |
+
{{- '<|im_start|>' + message.role + '\n<think>\n' + reasoning_content + '\n</think>\n\n' + content }}
|
| 102 |
+
{%- else %}
|
| 103 |
+
{{- '<|im_start|>' + message.role + '\n' + content }}
|
| 104 |
+
{%- endif %}
|
| 105 |
+
{%- if message.tool_calls and message.tool_calls is iterable and message.tool_calls is not mapping %}
|
| 106 |
+
{%- for tool_call in message.tool_calls %}
|
| 107 |
+
{%- if tool_call.function is defined %}
|
| 108 |
+
{%- set tool_call = tool_call.function %}
|
| 109 |
+
{%- endif %}
|
| 110 |
+
{%- if loop.first %}
|
| 111 |
+
{%- if content|trim %}
|
| 112 |
+
{{- '\n\n<tool_call>\n<function=' + tool_call.name + '>\n' }}
|
| 113 |
+
{%- else %}
|
| 114 |
+
{{- '<tool_call>\n<function=' + tool_call.name + '>\n' }}
|
| 115 |
+
{%- endif %}
|
| 116 |
+
{%- else %}
|
| 117 |
+
{{- '\n<tool_call>\n<function=' + tool_call.name + '>\n' }}
|
| 118 |
+
{%- endif %}
|
| 119 |
+
{%- if tool_call.arguments is defined %}
|
| 120 |
+
{%- for args_name, args_value in tool_call.arguments|items %}
|
| 121 |
+
{{- '<parameter=' + args_name + '>\n' }}
|
| 122 |
+
{%- set args_value = args_value | tojson | safe if args_value is mapping or (args_value is sequence and args_value is not string) else args_value | string %}
|
| 123 |
+
{{- args_value }}
|
| 124 |
+
{{- '\n</parameter>\n' }}
|
| 125 |
+
{%- endfor %}
|
| 126 |
+
{%- endif %}
|
| 127 |
+
{{- '</function>\n</tool_call>' }}
|
| 128 |
+
{%- endfor %}
|
| 129 |
+
{%- endif %}
|
| 130 |
+
{{- '<|im_end|>\n' }}
|
| 131 |
+
{%- elif message.role == "tool" %}
|
| 132 |
+
{%- if loop.previtem and loop.previtem.role != "tool" %}
|
| 133 |
+
{{- '<|im_start|>user' }}
|
| 134 |
+
{%- endif %}
|
| 135 |
+
{{- '\n<tool_response>\n' }}
|
| 136 |
+
{{- content }}
|
| 137 |
+
{{- '\n</tool_response>' }}
|
| 138 |
+
{%- if not loop.last and loop.nextitem.role != "tool" %}
|
| 139 |
+
{{- '<|im_end|>\n' }}
|
| 140 |
+
{%- elif loop.last %}
|
| 141 |
+
{{- '<|im_end|>\n' }}
|
| 142 |
+
{%- endif %}
|
| 143 |
+
{%- else %}
|
| 144 |
+
{{- raise_exception('Unexpected message role.') }}
|
| 145 |
+
{%- endif %}
|
| 146 |
+
{%- endfor %}
|
| 147 |
+
{%- if add_generation_prompt %}
|
| 148 |
+
{{- '<|im_start|>assistant\n' }}
|
| 149 |
+
{%- if enable_thinking is defined and enable_thinking is false %}
|
| 150 |
+
{{- '<think>\n\n</think>\n\n' }}
|
| 151 |
+
{%- else %}
|
| 152 |
+
{{- '<think>\n' }}
|
| 153 |
+
{%- endif %}
|
| 154 |
+
{%- endif %}
|
overgeneralisation_original_Swedish/Qwen3.5-4B-Base_overgeneralisation_splits_original_features_train_overgeneralisation_splits_original_features_test1/checkpoint-1120/tokenizer_config.json
ADDED
|
@@ -0,0 +1,31 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
{
|
| 2 |
+
"add_prefix_space": false,
|
| 3 |
+
"audio_bos_token": "<|audio_start|>",
|
| 4 |
+
"audio_eos_token": "<|audio_end|>",
|
| 5 |
+
"audio_token": "<|audio_pad|>",
|
| 6 |
+
"backend": "tokenizers",
|
| 7 |
+
"bos_token": null,
|
| 8 |
+
"clean_up_tokenization_spaces": false,
|
| 9 |
+
"eos_token": "<|endoftext|>",
|
| 10 |
+
"errors": "replace",
|
| 11 |
+
"image_token": "<|image_pad|>",
|
| 12 |
+
"is_local": false,
|
| 13 |
+
"model_max_length": 262144,
|
| 14 |
+
"model_specific_special_tokens": {
|
| 15 |
+
"audio_bos_token": "<|audio_start|>",
|
| 16 |
+
"audio_eos_token": "<|audio_end|>",
|
| 17 |
+
"audio_token": "<|audio_pad|>",
|
| 18 |
+
"image_token": "<|image_pad|>",
|
| 19 |
+
"video_token": "<|video_pad|>",
|
| 20 |
+
"vision_bos_token": "<|vision_start|>",
|
| 21 |
+
"vision_eos_token": "<|vision_end|>"
|
| 22 |
+
},
|
| 23 |
+
"pad_token": "<|endoftext|>",
|
| 24 |
+
"pretokenize_regex": "(?i:'s|'t|'re|'ve|'m|'ll|'d)|[^\\r\\n\\p{L}\\p{N}]?[\\p{L}\\p{M}]+|\\p{N}| ?[^\\s\\p{L}\\p{M}\\p{N}]+[\\r\\n]*|\\s*[\\r\\n]+|\\s+(?!\\S)|\\s+",
|
| 25 |
+
"split_special_tokens": false,
|
| 26 |
+
"tokenizer_class": "TokenizersBackend",
|
| 27 |
+
"unk_token": null,
|
| 28 |
+
"video_token": "<|video_pad|>",
|
| 29 |
+
"vision_bos_token": "<|vision_start|>",
|
| 30 |
+
"vision_eos_token": "<|vision_end|>"
|
| 31 |
+
}
|
overgeneralisation_original_Swedish/Qwen3.5-4B-Base_overgeneralisation_splits_original_features_train_overgeneralisation_splits_original_features_test1/checkpoint-1120/trainer_state.json
ADDED
|
@@ -0,0 +1,1210 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
{
|
| 2 |
+
"best_global_step": null,
|
| 3 |
+
"best_metric": null,
|
| 4 |
+
"best_model_checkpoint": null,
|
| 5 |
+
"epoch": 2.7870485678704857,
|
| 6 |
+
"eval_steps": 20,
|
| 7 |
+
"global_step": 1120,
|
| 8 |
+
"is_hyper_param_search": false,
|
| 9 |
+
"is_local_process_zero": true,
|
| 10 |
+
"is_world_process_zero": true,
|
| 11 |
+
"log_history": [
|
| 12 |
+
{
|
| 13 |
+
"entropy": 1.9784346982836722,
|
| 14 |
+
"epoch": 0.049813200498132,
|
| 15 |
+
"grad_norm": 3.0229668617248535,
|
| 16 |
+
"learning_rate": 9.526142962415369e-06,
|
| 17 |
+
"loss": 1.7360023498535155,
|
| 18 |
+
"mean_token_accuracy": 0.6449888605624438,
|
| 19 |
+
"num_tokens": 46794.0,
|
| 20 |
+
"step": 20
|
| 21 |
+
},
|
| 22 |
+
{
|
| 23 |
+
"epoch": 0.049813200498132,
|
| 24 |
+
"eval_entropy": 1.41506897571475,
|
| 25 |
+
"eval_loss": 1.1876318454742432,
|
| 26 |
+
"eval_mean_token_accuracy": 0.734131895525511,
|
| 27 |
+
"eval_num_tokens": 46794.0,
|
| 28 |
+
"eval_runtime": 87.8071,
|
| 29 |
+
"eval_samples_per_second": 15.671,
|
| 30 |
+
"eval_steps_per_second": 1.959,
|
| 31 |
+
"step": 20
|
| 32 |
+
},
|
| 33 |
+
{
|
| 34 |
+
"entropy": 1.049924298375845,
|
| 35 |
+
"epoch": 0.099626400996264,
|
| 36 |
+
"grad_norm": 1.5795097351074219,
|
| 37 |
+
"learning_rate": 1.9553661870221022e-05,
|
| 38 |
+
"loss": 0.8944448471069336,
|
| 39 |
+
"mean_token_accuracy": 0.7748479396104813,
|
| 40 |
+
"num_tokens": 90754.0,
|
| 41 |
+
"step": 40
|
| 42 |
+
},
|
| 43 |
+
{
|
| 44 |
+
"epoch": 0.099626400996264,
|
| 45 |
+
"eval_entropy": 0.7996658658565476,
|
| 46 |
+
"eval_loss": 0.7202735543251038,
|
| 47 |
+
"eval_mean_token_accuracy": 0.8070558306089667,
|
| 48 |
+
"eval_num_tokens": 90754.0,
|
| 49 |
+
"eval_runtime": 86.9199,
|
| 50 |
+
"eval_samples_per_second": 15.831,
|
| 51 |
+
"eval_steps_per_second": 1.979,
|
| 52 |
+
"step": 40
|
| 53 |
+
},
|
| 54 |
+
{
|
| 55 |
+
"entropy": 0.7734908878803253,
|
| 56 |
+
"epoch": 0.149439601494396,
|
| 57 |
+
"grad_norm": 1.3136248588562012,
|
| 58 |
+
"learning_rate": 2.9581180778026673e-05,
|
| 59 |
+
"loss": 0.6780608654022217,
|
| 60 |
+
"mean_token_accuracy": 0.8168170280754566,
|
| 61 |
+
"num_tokens": 137472.0,
|
| 62 |
+
"step": 60
|
| 63 |
+
},
|
| 64 |
+
{
|
| 65 |
+
"epoch": 0.149439601494396,
|
| 66 |
+
"eval_entropy": 0.7119324009778888,
|
| 67 |
+
"eval_loss": 0.6554311513900757,
|
| 68 |
+
"eval_mean_token_accuracy": 0.8215604798738346,
|
| 69 |
+
"eval_num_tokens": 137472.0,
|
| 70 |
+
"eval_runtime": 86.8692,
|
| 71 |
+
"eval_samples_per_second": 15.84,
|
| 72 |
+
"eval_steps_per_second": 1.98,
|
| 73 |
+
"step": 60
|
| 74 |
+
},
|
| 75 |
+
{
|
| 76 |
+
"entropy": 0.7071127541363239,
|
| 77 |
+
"epoch": 0.199252801992528,
|
| 78 |
+
"grad_norm": 1.387060284614563,
|
| 79 |
+
"learning_rate": 3.960869968583232e-05,
|
| 80 |
+
"loss": 0.6382100582122803,
|
| 81 |
+
"mean_token_accuracy": 0.8229366384446621,
|
| 82 |
+
"num_tokens": 187408.0,
|
| 83 |
+
"step": 80
|
| 84 |
+
},
|
| 85 |
+
{
|
| 86 |
+
"epoch": 0.199252801992528,
|
| 87 |
+
"eval_entropy": 0.6883931482254073,
|
| 88 |
+
"eval_loss": 0.625065803527832,
|
| 89 |
+
"eval_mean_token_accuracy": 0.828940509710201,
|
| 90 |
+
"eval_num_tokens": 187408.0,
|
| 91 |
+
"eval_runtime": 86.662,
|
| 92 |
+
"eval_samples_per_second": 15.878,
|
| 93 |
+
"eval_steps_per_second": 1.985,
|
| 94 |
+
"step": 80
|
| 95 |
+
},
|
| 96 |
+
{
|
| 97 |
+
"entropy": 0.6800824083387852,
|
| 98 |
+
"epoch": 0.24906600249066002,
|
| 99 |
+
"grad_norm": 0.9892916679382324,
|
| 100 |
+
"learning_rate": 4.963621859363797e-05,
|
| 101 |
+
"loss": 0.6011715888977051,
|
| 102 |
+
"mean_token_accuracy": 0.8323964163661003,
|
| 103 |
+
"num_tokens": 234197.0,
|
| 104 |
+
"step": 100
|
| 105 |
+
},
|
| 106 |
+
{
|
| 107 |
+
"epoch": 0.24906600249066002,
|
| 108 |
+
"eval_entropy": 0.6840810470802839,
|
| 109 |
+
"eval_loss": 0.6037028431892395,
|
| 110 |
+
"eval_mean_token_accuracy": 0.8309669033732525,
|
| 111 |
+
"eval_num_tokens": 234197.0,
|
| 112 |
+
"eval_runtime": 86.4637,
|
| 113 |
+
"eval_samples_per_second": 15.914,
|
| 114 |
+
"eval_steps_per_second": 1.989,
|
| 115 |
+
"step": 100
|
| 116 |
+
},
|
| 117 |
+
{
|
| 118 |
+
"entropy": 0.6776216626167297,
|
| 119 |
+
"epoch": 0.298879202988792,
|
| 120 |
+
"grad_norm": 0.8918434977531433,
|
| 121 |
+
"learning_rate": 5.9663737501443624e-05,
|
| 122 |
+
"loss": 0.5991742610931396,
|
| 123 |
+
"mean_token_accuracy": 0.8300838828086853,
|
| 124 |
+
"num_tokens": 281241.0,
|
| 125 |
+
"step": 120
|
| 126 |
+
},
|
| 127 |
+
{
|
| 128 |
+
"epoch": 0.298879202988792,
|
| 129 |
+
"eval_entropy": 0.690427724705186,
|
| 130 |
+
"eval_loss": 0.5939701795578003,
|
| 131 |
+
"eval_mean_token_accuracy": 0.8345950186945671,
|
| 132 |
+
"eval_num_tokens": 281241.0,
|
| 133 |
+
"eval_runtime": 86.6626,
|
| 134 |
+
"eval_samples_per_second": 15.878,
|
| 135 |
+
"eval_steps_per_second": 1.985,
|
| 136 |
+
"step": 120
|
| 137 |
+
},
|
| 138 |
+
{
|
| 139 |
+
"entropy": 0.6709842771291733,
|
| 140 |
+
"epoch": 0.34869240348692404,
|
| 141 |
+
"grad_norm": 0.9135531187057495,
|
| 142 |
+
"learning_rate": 6.969125640924927e-05,
|
| 143 |
+
"loss": 0.5914147377014161,
|
| 144 |
+
"mean_token_accuracy": 0.8314545609056949,
|
| 145 |
+
"num_tokens": 327393.0,
|
| 146 |
+
"step": 140
|
| 147 |
+
},
|
| 148 |
+
{
|
| 149 |
+
"epoch": 0.34869240348692404,
|
| 150 |
+
"eval_entropy": 0.6584504666023476,
|
| 151 |
+
"eval_loss": 0.5849721431732178,
|
| 152 |
+
"eval_mean_token_accuracy": 0.8357757236375365,
|
| 153 |
+
"eval_num_tokens": 327393.0,
|
| 154 |
+
"eval_runtime": 86.3262,
|
| 155 |
+
"eval_samples_per_second": 15.94,
|
| 156 |
+
"eval_steps_per_second": 1.992,
|
| 157 |
+
"step": 140
|
| 158 |
+
},
|
| 159 |
+
{
|
| 160 |
+
"entropy": 0.6524647936224938,
|
| 161 |
+
"epoch": 0.398505603985056,
|
| 162 |
+
"grad_norm": 0.8651587963104248,
|
| 163 |
+
"learning_rate": 7.971877531705493e-05,
|
| 164 |
+
"loss": 0.5710843563079834,
|
| 165 |
+
"mean_token_accuracy": 0.8396127380430698,
|
| 166 |
+
"num_tokens": 373834.0,
|
| 167 |
+
"step": 160
|
| 168 |
+
},
|
| 169 |
+
{
|
| 170 |
+
"epoch": 0.398505603985056,
|
| 171 |
+
"eval_entropy": 0.6283470298661742,
|
| 172 |
+
"eval_loss": 0.5738973617553711,
|
| 173 |
+
"eval_mean_token_accuracy": 0.8379981181649274,
|
| 174 |
+
"eval_num_tokens": 373834.0,
|
| 175 |
+
"eval_runtime": 86.5619,
|
| 176 |
+
"eval_samples_per_second": 15.896,
|
| 177 |
+
"eval_steps_per_second": 1.987,
|
| 178 |
+
"step": 160
|
| 179 |
+
},
|
| 180 |
+
{
|
| 181 |
+
"entropy": 0.6450445972383022,
|
| 182 |
+
"epoch": 0.44831880448318806,
|
| 183 |
+
"grad_norm": 0.8661723732948303,
|
| 184 |
+
"learning_rate": 8.974629422486058e-05,
|
| 185 |
+
"loss": 0.5677794933319091,
|
| 186 |
+
"mean_token_accuracy": 0.8389350369572639,
|
| 187 |
+
"num_tokens": 422572.0,
|
| 188 |
+
"step": 180
|
| 189 |
+
},
|
| 190 |
+
{
|
| 191 |
+
"epoch": 0.44831880448318806,
|
| 192 |
+
"eval_entropy": 0.6142613257086554,
|
| 193 |
+
"eval_loss": 0.5698265433311462,
|
| 194 |
+
"eval_mean_token_accuracy": 0.8388577273418737,
|
| 195 |
+
"eval_num_tokens": 422572.0,
|
| 196 |
+
"eval_runtime": 86.4443,
|
| 197 |
+
"eval_samples_per_second": 15.918,
|
| 198 |
+
"eval_steps_per_second": 1.99,
|
| 199 |
+
"step": 180
|
| 200 |
+
},
|
| 201 |
+
{
|
| 202 |
+
"entropy": 0.6448334597051144,
|
| 203 |
+
"epoch": 0.49813200498132004,
|
| 204 |
+
"grad_norm": 0.9662242531776428,
|
| 205 |
+
"learning_rate": 9.977381313266624e-05,
|
| 206 |
+
"loss": 0.581433916091919,
|
| 207 |
+
"mean_token_accuracy": 0.8387043006718159,
|
| 208 |
+
"num_tokens": 471879.0,
|
| 209 |
+
"step": 200
|
| 210 |
+
},
|
| 211 |
+
{
|
| 212 |
+
"epoch": 0.49813200498132004,
|
| 213 |
+
"eval_entropy": 0.6154296522916749,
|
| 214 |
+
"eval_loss": 0.5660303831100464,
|
| 215 |
+
"eval_mean_token_accuracy": 0.8412494766850804,
|
| 216 |
+
"eval_num_tokens": 471879.0,
|
| 217 |
+
"eval_runtime": 86.3063,
|
| 218 |
+
"eval_samples_per_second": 15.943,
|
| 219 |
+
"eval_steps_per_second": 1.993,
|
| 220 |
+
"step": 200
|
| 221 |
+
},
|
| 222 |
+
{
|
| 223 |
+
"entropy": 0.6376728117465973,
|
| 224 |
+
"epoch": 0.547945205479452,
|
| 225 |
+
"grad_norm": 0.7618638873100281,
|
| 226 |
+
"learning_rate": 0.00010980133204047189,
|
| 227 |
+
"loss": 0.5678351402282715,
|
| 228 |
+
"mean_token_accuracy": 0.8404546812176704,
|
| 229 |
+
"num_tokens": 520984.0,
|
| 230 |
+
"step": 220
|
| 231 |
+
},
|
| 232 |
+
{
|
| 233 |
+
"epoch": 0.547945205479452,
|
| 234 |
+
"eval_entropy": 0.6181817033956217,
|
| 235 |
+
"eval_loss": 0.5663750171661377,
|
| 236 |
+
"eval_mean_token_accuracy": 0.8388350962899452,
|
| 237 |
+
"eval_num_tokens": 520984.0,
|
| 238 |
+
"eval_runtime": 86.5904,
|
| 239 |
+
"eval_samples_per_second": 15.891,
|
| 240 |
+
"eval_steps_per_second": 1.986,
|
| 241 |
+
"step": 220
|
| 242 |
+
},
|
| 243 |
+
{
|
| 244 |
+
"entropy": 0.6303176879882812,
|
| 245 |
+
"epoch": 0.597758405977584,
|
| 246 |
+
"grad_norm": 0.7571695446968079,
|
| 247 |
+
"learning_rate": 0.00011982885094827753,
|
| 248 |
+
"loss": 0.5502778053283691,
|
| 249 |
+
"mean_token_accuracy": 0.8429657347500324,
|
| 250 |
+
"num_tokens": 566596.0,
|
| 251 |
+
"step": 240
|
| 252 |
+
},
|
| 253 |
+
{
|
| 254 |
+
"epoch": 0.597758405977584,
|
| 255 |
+
"eval_entropy": 0.6252533817707107,
|
| 256 |
+
"eval_loss": 0.5570284128189087,
|
| 257 |
+
"eval_mean_token_accuracy": 0.8427327847064927,
|
| 258 |
+
"eval_num_tokens": 566596.0,
|
| 259 |
+
"eval_runtime": 86.4157,
|
| 260 |
+
"eval_samples_per_second": 15.923,
|
| 261 |
+
"eval_steps_per_second": 1.99,
|
| 262 |
+
"step": 240
|
| 263 |
+
},
|
| 264 |
+
{
|
| 265 |
+
"entropy": 0.6202544964849949,
|
| 266 |
+
"epoch": 0.6475716064757161,
|
| 267 |
+
"grad_norm": 0.6447190642356873,
|
| 268 |
+
"learning_rate": 0.00012985636985608318,
|
| 269 |
+
"loss": 0.5485352993011474,
|
| 270 |
+
"mean_token_accuracy": 0.844165726006031,
|
| 271 |
+
"num_tokens": 613603.0,
|
| 272 |
+
"step": 260
|
| 273 |
+
},
|
| 274 |
+
{
|
| 275 |
+
"epoch": 0.6475716064757161,
|
| 276 |
+
"eval_entropy": 0.6441633552312851,
|
| 277 |
+
"eval_loss": 0.5606644153594971,
|
| 278 |
+
"eval_mean_token_accuracy": 0.842403513054515,
|
| 279 |
+
"eval_num_tokens": 613603.0,
|
| 280 |
+
"eval_runtime": 86.6343,
|
| 281 |
+
"eval_samples_per_second": 15.883,
|
| 282 |
+
"eval_steps_per_second": 1.985,
|
| 283 |
+
"step": 260
|
| 284 |
+
},
|
| 285 |
+
{
|
| 286 |
+
"entropy": 0.6306711677461863,
|
| 287 |
+
"epoch": 0.6973848069738481,
|
| 288 |
+
"grad_norm": 0.7869907021522522,
|
| 289 |
+
"learning_rate": 0.00013988388876388883,
|
| 290 |
+
"loss": 0.5579307556152344,
|
| 291 |
+
"mean_token_accuracy": 0.841247134655714,
|
| 292 |
+
"num_tokens": 658565.0,
|
| 293 |
+
"step": 280
|
| 294 |
+
},
|
| 295 |
+
{
|
| 296 |
+
"epoch": 0.6973848069738481,
|
| 297 |
+
"eval_entropy": 0.6263934678809587,
|
| 298 |
+
"eval_loss": 0.5559113025665283,
|
| 299 |
+
"eval_mean_token_accuracy": 0.8427334743183713,
|
| 300 |
+
"eval_num_tokens": 658565.0,
|
| 301 |
+
"eval_runtime": 86.6403,
|
| 302 |
+
"eval_samples_per_second": 15.882,
|
| 303 |
+
"eval_steps_per_second": 1.985,
|
| 304 |
+
"step": 280
|
| 305 |
+
},
|
| 306 |
+
{
|
| 307 |
+
"entropy": 0.6385872110724449,
|
| 308 |
+
"epoch": 0.7471980074719801,
|
| 309 |
+
"grad_norm": 0.6679229736328125,
|
| 310 |
+
"learning_rate": 0.0001499114076716945,
|
| 311 |
+
"loss": 0.5667279720306396,
|
| 312 |
+
"mean_token_accuracy": 0.8389136254787445,
|
| 313 |
+
"num_tokens": 705680.0,
|
| 314 |
+
"step": 300
|
| 315 |
+
},
|
| 316 |
+
{
|
| 317 |
+
"epoch": 0.7471980074719801,
|
| 318 |
+
"eval_entropy": 0.6141417321077612,
|
| 319 |
+
"eval_loss": 0.5570600628852844,
|
| 320 |
+
"eval_mean_token_accuracy": 0.8437647996253745,
|
| 321 |
+
"eval_num_tokens": 705680.0,
|
| 322 |
+
"eval_runtime": 86.7588,
|
| 323 |
+
"eval_samples_per_second": 15.86,
|
| 324 |
+
"eval_steps_per_second": 1.983,
|
| 325 |
+
"step": 300
|
| 326 |
+
},
|
| 327 |
+
{
|
| 328 |
+
"entropy": 0.6199494235217571,
|
| 329 |
+
"epoch": 0.797011207970112,
|
| 330 |
+
"grad_norm": 0.7924400568008423,
|
| 331 |
+
"learning_rate": 0.00015993892657950015,
|
| 332 |
+
"loss": 0.5529299736022949,
|
| 333 |
+
"mean_token_accuracy": 0.8426973208785057,
|
| 334 |
+
"num_tokens": 752616.0,
|
| 335 |
+
"step": 320
|
| 336 |
+
},
|
| 337 |
+
{
|
| 338 |
+
"epoch": 0.797011207970112,
|
| 339 |
+
"eval_entropy": 0.6133768925833147,
|
| 340 |
+
"eval_loss": 0.556602418422699,
|
| 341 |
+
"eval_mean_token_accuracy": 0.8432947965555413,
|
| 342 |
+
"eval_num_tokens": 752616.0,
|
| 343 |
+
"eval_runtime": 86.492,
|
| 344 |
+
"eval_samples_per_second": 15.909,
|
| 345 |
+
"eval_steps_per_second": 1.989,
|
| 346 |
+
"step": 320
|
| 347 |
+
},
|
| 348 |
+
{
|
| 349 |
+
"entropy": 0.6203986253589392,
|
| 350 |
+
"epoch": 0.8468244084682441,
|
| 351 |
+
"grad_norm": 0.8364354372024536,
|
| 352 |
+
"learning_rate": 0.00016996644548730578,
|
| 353 |
+
"loss": 0.5551144123077393,
|
| 354 |
+
"mean_token_accuracy": 0.8432973213493824,
|
| 355 |
+
"num_tokens": 797151.0,
|
| 356 |
+
"step": 340
|
| 357 |
+
},
|
| 358 |
+
{
|
| 359 |
+
"epoch": 0.8468244084682441,
|
| 360 |
+
"eval_entropy": 0.6017442844634833,
|
| 361 |
+
"eval_loss": 0.5566568374633789,
|
| 362 |
+
"eval_mean_token_accuracy": 0.8437666123689607,
|
| 363 |
+
"eval_num_tokens": 797151.0,
|
| 364 |
+
"eval_runtime": 86.5552,
|
| 365 |
+
"eval_samples_per_second": 15.897,
|
| 366 |
+
"eval_steps_per_second": 1.987,
|
| 367 |
+
"step": 340
|
| 368 |
+
},
|
| 369 |
+
{
|
| 370 |
+
"entropy": 0.6341533534228802,
|
| 371 |
+
"epoch": 0.8966376089663761,
|
| 372 |
+
"grad_norm": 0.7783445715904236,
|
| 373 |
+
"learning_rate": 0.00017999396439511144,
|
| 374 |
+
"loss": 0.5669133186340332,
|
| 375 |
+
"mean_token_accuracy": 0.8379446342587471,
|
| 376 |
+
"num_tokens": 843585.0,
|
| 377 |
+
"step": 360
|
| 378 |
+
},
|
| 379 |
+
{
|
| 380 |
+
"epoch": 0.8966376089663761,
|
| 381 |
+
"eval_entropy": 0.6055107958788095,
|
| 382 |
+
"eval_loss": 0.5599350333213806,
|
| 383 |
+
"eval_mean_token_accuracy": 0.8435030894917112,
|
| 384 |
+
"eval_num_tokens": 843585.0,
|
| 385 |
+
"eval_runtime": 86.4814,
|
| 386 |
+
"eval_samples_per_second": 15.911,
|
| 387 |
+
"eval_steps_per_second": 1.989,
|
| 388 |
+
"step": 360
|
| 389 |
+
},
|
| 390 |
+
{
|
| 391 |
+
"entropy": 0.6306198488920927,
|
| 392 |
+
"epoch": 0.9464508094645081,
|
| 393 |
+
"grad_norm": 0.8449786901473999,
|
| 394 |
+
"learning_rate": 0.0001900214833029171,
|
| 395 |
+
"loss": 0.5739435195922852,
|
| 396 |
+
"mean_token_accuracy": 0.8393832489848136,
|
| 397 |
+
"num_tokens": 889842.0,
|
| 398 |
+
"step": 380
|
| 399 |
+
},
|
| 400 |
+
{
|
| 401 |
+
"epoch": 0.9464508094645081,
|
| 402 |
+
"eval_entropy": 0.6129532439071078,
|
| 403 |
+
"eval_loss": 0.5566295981407166,
|
| 404 |
+
"eval_mean_token_accuracy": 0.8430350880290187,
|
| 405 |
+
"eval_num_tokens": 889842.0,
|
| 406 |
+
"eval_runtime": 86.4643,
|
| 407 |
+
"eval_samples_per_second": 15.914,
|
| 408 |
+
"eval_steps_per_second": 1.989,
|
| 409 |
+
"step": 380
|
| 410 |
+
},
|
| 411 |
+
{
|
| 412 |
+
"entropy": 0.6203123550862074,
|
| 413 |
+
"epoch": 0.9962640099626401,
|
| 414 |
+
"grad_norm": 0.7334314584732056,
|
| 415 |
+
"learning_rate": 0.00020004900221072276,
|
| 416 |
+
"loss": 0.5547565937042236,
|
| 417 |
+
"mean_token_accuracy": 0.8403573960065842,
|
| 418 |
+
"num_tokens": 935589.0,
|
| 419 |
+
"step": 400
|
| 420 |
+
},
|
| 421 |
+
{
|
| 422 |
+
"epoch": 0.9962640099626401,
|
| 423 |
+
"eval_entropy": 0.6275761647279873,
|
| 424 |
+
"eval_loss": 0.5621116757392883,
|
| 425 |
+
"eval_mean_token_accuracy": 0.841587379228237,
|
| 426 |
+
"eval_num_tokens": 935589.0,
|
| 427 |
+
"eval_runtime": 86.4748,
|
| 428 |
+
"eval_samples_per_second": 15.912,
|
| 429 |
+
"eval_steps_per_second": 1.989,
|
| 430 |
+
"step": 400
|
| 431 |
+
},
|
| 432 |
+
{
|
| 433 |
+
"entropy": 0.5795013002860241,
|
| 434 |
+
"epoch": 1.0448318804483188,
|
| 435 |
+
"grad_norm": 0.8858296871185303,
|
| 436 |
+
"learning_rate": 0.0002015421505577756,
|
| 437 |
+
"loss": 0.5183939933776855,
|
| 438 |
+
"mean_token_accuracy": 0.850081592034071,
|
| 439 |
+
"num_tokens": 980589.0,
|
| 440 |
+
"step": 420
|
| 441 |
+
},
|
| 442 |
+
{
|
| 443 |
+
"epoch": 1.0448318804483188,
|
| 444 |
+
"eval_entropy": 0.5583065545489622,
|
| 445 |
+
"eval_loss": 0.5605642199516296,
|
| 446 |
+
"eval_mean_token_accuracy": 0.8439708411000496,
|
| 447 |
+
"eval_num_tokens": 980589.0,
|
| 448 |
+
"eval_runtime": 86.5422,
|
| 449 |
+
"eval_samples_per_second": 15.9,
|
| 450 |
+
"eval_steps_per_second": 1.987,
|
| 451 |
+
"step": 420
|
| 452 |
+
},
|
| 453 |
+
{
|
| 454 |
+
"entropy": 0.5671238023787737,
|
| 455 |
+
"epoch": 1.0946450809464507,
|
| 456 |
+
"grad_norm": 0.6882498264312744,
|
| 457 |
+
"learning_rate": 0.00020150112347025443,
|
| 458 |
+
"loss": 0.5077326774597168,
|
| 459 |
+
"mean_token_accuracy": 0.8489868573844432,
|
| 460 |
+
"num_tokens": 1027852.0,
|
| 461 |
+
"step": 440
|
| 462 |
+
},
|
| 463 |
+
{
|
| 464 |
+
"epoch": 1.0946450809464507,
|
| 465 |
+
"eval_entropy": 0.5868900277933409,
|
| 466 |
+
"eval_loss": 0.5602695345878601,
|
| 467 |
+
"eval_mean_token_accuracy": 0.8428842161977014,
|
| 468 |
+
"eval_num_tokens": 1027852.0,
|
| 469 |
+
"eval_runtime": 86.623,
|
| 470 |
+
"eval_samples_per_second": 15.885,
|
| 471 |
+
"eval_steps_per_second": 1.986,
|
| 472 |
+
"step": 440
|
| 473 |
+
},
|
| 474 |
+
{
|
| 475 |
+
"entropy": 0.5533561781048775,
|
| 476 |
+
"epoch": 1.1444582814445827,
|
| 477 |
+
"grad_norm": 0.7717723250389099,
|
| 478 |
+
"learning_rate": 0.0002014297192297181,
|
| 479 |
+
"loss": 0.4954517364501953,
|
| 480 |
+
"mean_token_accuracy": 0.8529035650193691,
|
| 481 |
+
"num_tokens": 1077649.0,
|
| 482 |
+
"step": 460
|
| 483 |
+
},
|
| 484 |
+
{
|
| 485 |
+
"epoch": 1.1444582814445827,
|
| 486 |
+
"eval_entropy": 0.5600803743961246,
|
| 487 |
+
"eval_loss": 0.5608077645301819,
|
| 488 |
+
"eval_mean_token_accuracy": 0.8445036771685578,
|
| 489 |
+
"eval_num_tokens": 1077649.0,
|
| 490 |
+
"eval_runtime": 86.1316,
|
| 491 |
+
"eval_samples_per_second": 15.976,
|
| 492 |
+
"eval_steps_per_second": 1.997,
|
| 493 |
+
"step": 460
|
| 494 |
+
},
|
| 495 |
+
{
|
| 496 |
+
"entropy": 0.5692154694348573,
|
| 497 |
+
"epoch": 1.1942714819427147,
|
| 498 |
+
"grad_norm": 0.7322827577590942,
|
| 499 |
+
"learning_rate": 0.0002013279593707117,
|
| 500 |
+
"loss": 0.505049467086792,
|
| 501 |
+
"mean_token_accuracy": 0.8551576808094978,
|
| 502 |
+
"num_tokens": 1124872.0,
|
| 503 |
+
"step": 480
|
| 504 |
+
},
|
| 505 |
+
{
|
| 506 |
+
"epoch": 1.1942714819427147,
|
| 507 |
+
"eval_entropy": 0.5732695829383162,
|
| 508 |
+
"eval_loss": 0.5594323873519897,
|
| 509 |
+
"eval_mean_token_accuracy": 0.8449713407560836,
|
| 510 |
+
"eval_num_tokens": 1124872.0,
|
| 511 |
+
"eval_runtime": 86.2726,
|
| 512 |
+
"eval_samples_per_second": 15.949,
|
| 513 |
+
"eval_steps_per_second": 1.994,
|
| 514 |
+
"step": 480
|
| 515 |
+
},
|
| 516 |
+
{
|
| 517 |
+
"entropy": 0.5817618492990733,
|
| 518 |
+
"epoch": 1.244084682440847,
|
| 519 |
+
"grad_norm": 1.1776764392852783,
|
| 520 |
+
"learning_rate": 0.0002011958745826208,
|
| 521 |
+
"loss": 0.5137609958648681,
|
| 522 |
+
"mean_token_accuracy": 0.8521522544324398,
|
| 523 |
+
"num_tokens": 1168698.0,
|
| 524 |
+
"step": 500
|
| 525 |
+
},
|
| 526 |
+
{
|
| 527 |
+
"epoch": 1.244084682440847,
|
| 528 |
+
"eval_entropy": 0.5662581343636957,
|
| 529 |
+
"eval_loss": 0.5595026016235352,
|
| 530 |
+
"eval_mean_token_accuracy": 0.8441977164773053,
|
| 531 |
+
"eval_num_tokens": 1168698.0,
|
| 532 |
+
"eval_runtime": 86.7261,
|
| 533 |
+
"eval_samples_per_second": 15.866,
|
| 534 |
+
"eval_steps_per_second": 1.983,
|
| 535 |
+
"step": 500
|
| 536 |
+
},
|
| 537 |
+
{
|
| 538 |
+
"entropy": 0.5712925456464291,
|
| 539 |
+
"epoch": 1.293897882938979,
|
| 540 |
+
"grad_norm": 0.7960361838340759,
|
| 541 |
+
"learning_rate": 0.0002010335047004159,
|
| 542 |
+
"loss": 0.5134767532348633,
|
| 543 |
+
"mean_token_accuracy": 0.8513577707111836,
|
| 544 |
+
"num_tokens": 1216679.0,
|
| 545 |
+
"step": 520
|
| 546 |
+
},
|
| 547 |
+
{
|
| 548 |
+
"epoch": 1.293897882938979,
|
| 549 |
+
"eval_entropy": 0.5441222797299541,
|
| 550 |
+
"eval_loss": 0.5535460114479065,
|
| 551 |
+
"eval_mean_token_accuracy": 0.8450886118550633,
|
| 552 |
+
"eval_num_tokens": 1216679.0,
|
| 553 |
+
"eval_runtime": 86.2675,
|
| 554 |
+
"eval_samples_per_second": 15.95,
|
| 555 |
+
"eval_steps_per_second": 1.994,
|
| 556 |
+
"step": 520
|
| 557 |
+
},
|
| 558 |
+
{
|
| 559 |
+
"entropy": 0.5787045754492283,
|
| 560 |
+
"epoch": 1.3437110834371109,
|
| 561 |
+
"grad_norm": 0.9205410480499268,
|
| 562 |
+
"learning_rate": 0.00020084089869263887,
|
| 563 |
+
"loss": 0.5119701862335205,
|
| 564 |
+
"mean_token_accuracy": 0.8503516331315041,
|
| 565 |
+
"num_tokens": 1261365.0,
|
| 566 |
+
"step": 540
|
| 567 |
+
},
|
| 568 |
+
{
|
| 569 |
+
"epoch": 1.3437110834371109,
|
| 570 |
+
"eval_entropy": 0.5744457827057949,
|
| 571 |
+
"eval_loss": 0.5514978766441345,
|
| 572 |
+
"eval_mean_token_accuracy": 0.845929987901865,
|
| 573 |
+
"eval_num_tokens": 1261365.0,
|
| 574 |
+
"eval_runtime": 86.2299,
|
| 575 |
+
"eval_samples_per_second": 15.957,
|
| 576 |
+
"eval_steps_per_second": 1.995,
|
| 577 |
+
"step": 540
|
| 578 |
+
},
|
| 579 |
+
{
|
| 580 |
+
"entropy": 0.5739392962306737,
|
| 581 |
+
"epoch": 1.3935242839352429,
|
| 582 |
+
"grad_norm": 0.7475653886795044,
|
| 583 |
+
"learning_rate": 0.00020061811464663464,
|
| 584 |
+
"loss": 0.5189042091369629,
|
| 585 |
+
"mean_token_accuracy": 0.8492388024926185,
|
| 586 |
+
"num_tokens": 1306879.0,
|
| 587 |
+
"step": 560
|
| 588 |
+
},
|
| 589 |
+
{
|
| 590 |
+
"epoch": 1.3935242839352429,
|
| 591 |
+
"eval_entropy": 0.6116398271433142,
|
| 592 |
+
"eval_loss": 0.551732063293457,
|
| 593 |
+
"eval_mean_token_accuracy": 0.8450756967067719,
|
| 594 |
+
"eval_num_tokens": 1306879.0,
|
| 595 |
+
"eval_runtime": 86.6081,
|
| 596 |
+
"eval_samples_per_second": 15.888,
|
| 597 |
+
"eval_steps_per_second": 1.986,
|
| 598 |
+
"step": 560
|
| 599 |
+
},
|
| 600 |
+
{
|
| 601 |
+
"entropy": 0.5755622573196888,
|
| 602 |
+
"epoch": 1.4433374844333748,
|
| 603 |
+
"grad_norm": 0.8218411803245544,
|
| 604 |
+
"learning_rate": 0.00020036521975103286,
|
| 605 |
+
"loss": 0.5106248378753662,
|
| 606 |
+
"mean_token_accuracy": 0.8506785586476326,
|
| 607 |
+
"num_tokens": 1353534.0,
|
| 608 |
+
"step": 580
|
| 609 |
+
},
|
| 610 |
+
{
|
| 611 |
+
"epoch": 1.4433374844333748,
|
| 612 |
+
"eval_entropy": 0.5906928708386976,
|
| 613 |
+
"eval_loss": 0.551278829574585,
|
| 614 |
+
"eval_mean_token_accuracy": 0.8462819308042526,
|
| 615 |
+
"eval_num_tokens": 1353534.0,
|
| 616 |
+
"eval_runtime": 86.5438,
|
| 617 |
+
"eval_samples_per_second": 15.899,
|
| 618 |
+
"eval_steps_per_second": 1.987,
|
| 619 |
+
"step": 580
|
| 620 |
+
},
|
| 621 |
+
{
|
| 622 |
+
"entropy": 0.5694822132587433,
|
| 623 |
+
"epoch": 1.4931506849315068,
|
| 624 |
+
"grad_norm": 0.8880652189254761,
|
| 625 |
+
"learning_rate": 0.00020008229027548475,
|
| 626 |
+
"loss": 0.5140334606170655,
|
| 627 |
+
"mean_token_accuracy": 0.8521522797644139,
|
| 628 |
+
"num_tokens": 1399537.0,
|
| 629 |
+
"step": 600
|
| 630 |
+
},
|
| 631 |
+
{
|
| 632 |
+
"epoch": 1.4931506849315068,
|
| 633 |
+
"eval_entropy": 0.5599641964532608,
|
| 634 |
+
"eval_loss": 0.5501875877380371,
|
| 635 |
+
"eval_mean_token_accuracy": 0.8467660788879838,
|
| 636 |
+
"eval_num_tokens": 1399537.0,
|
| 637 |
+
"eval_runtime": 86.6458,
|
| 638 |
+
"eval_samples_per_second": 15.881,
|
| 639 |
+
"eval_steps_per_second": 1.985,
|
| 640 |
+
"step": 600
|
| 641 |
+
},
|
| 642 |
+
{
|
| 643 |
+
"entropy": 0.5675108034163714,
|
| 644 |
+
"epoch": 1.5429638854296388,
|
| 645 |
+
"grad_norm": 0.837087094783783,
|
| 646 |
+
"learning_rate": 0.0001997694115476612,
|
| 647 |
+
"loss": 0.5099846363067627,
|
| 648 |
+
"mean_token_accuracy": 0.8543680295348167,
|
| 649 |
+
"num_tokens": 1448422.0,
|
| 650 |
+
"step": 620
|
| 651 |
+
},
|
| 652 |
+
{
|
| 653 |
+
"epoch": 1.5429638854296388,
|
| 654 |
+
"eval_entropy": 0.5728072581249614,
|
| 655 |
+
"eval_loss": 0.5445425510406494,
|
| 656 |
+
"eval_mean_token_accuracy": 0.8474342175001321,
|
| 657 |
+
"eval_num_tokens": 1448422.0,
|
| 658 |
+
"eval_runtime": 86.4859,
|
| 659 |
+
"eval_samples_per_second": 15.91,
|
| 660 |
+
"eval_steps_per_second": 1.989,
|
| 661 |
+
"step": 620
|
| 662 |
+
},
|
| 663 |
+
{
|
| 664 |
+
"entropy": 0.5700885068625212,
|
| 665 |
+
"epoch": 1.592777085927771,
|
| 666 |
+
"grad_norm": 0.6598765850067139,
|
| 667 |
+
"learning_rate": 0.000199426677927519,
|
| 668 |
+
"loss": 0.5122694969177246,
|
| 669 |
+
"mean_token_accuracy": 0.8519927568733692,
|
| 670 |
+
"num_tokens": 1495009.0,
|
| 671 |
+
"step": 640
|
| 672 |
+
},
|
| 673 |
+
{
|
| 674 |
+
"epoch": 1.592777085927771,
|
| 675 |
+
"eval_entropy": 0.5476993622128353,
|
| 676 |
+
"eval_loss": 0.5427973866462708,
|
| 677 |
+
"eval_mean_token_accuracy": 0.8478512147138285,
|
| 678 |
+
"eval_num_tokens": 1495009.0,
|
| 679 |
+
"eval_runtime": 86.4172,
|
| 680 |
+
"eval_samples_per_second": 15.923,
|
| 681 |
+
"eval_steps_per_second": 1.99,
|
| 682 |
+
"step": 640
|
| 683 |
+
},
|
| 684 |
+
{
|
| 685 |
+
"entropy": 0.5829229176044464,
|
| 686 |
+
"epoch": 1.6425902864259028,
|
| 687 |
+
"grad_norm": 0.6965194940567017,
|
| 688 |
+
"learning_rate": 0.00019905419277884342,
|
| 689 |
+
"loss": 0.5253659725189209,
|
| 690 |
+
"mean_token_accuracy": 0.8493309423327446,
|
| 691 |
+
"num_tokens": 1536932.0,
|
| 692 |
+
"step": 660
|
| 693 |
+
},
|
| 694 |
+
{
|
| 695 |
+
"epoch": 1.6425902864259028,
|
| 696 |
+
"eval_entropy": 0.5666290084983028,
|
| 697 |
+
"eval_loss": 0.5467478036880493,
|
| 698 |
+
"eval_mean_token_accuracy": 0.8479407703460649,
|
| 699 |
+
"eval_num_tokens": 1536932.0,
|
| 700 |
+
"eval_runtime": 86.4414,
|
| 701 |
+
"eval_samples_per_second": 15.918,
|
| 702 |
+
"eval_steps_per_second": 1.99,
|
| 703 |
+
"step": 660
|
| 704 |
+
},
|
| 705 |
+
{
|
| 706 |
+
"entropy": 0.5498311135917902,
|
| 707 |
+
"epoch": 1.692403486924035,
|
| 708 |
+
"grad_norm": 0.636583685874939,
|
| 709 |
+
"learning_rate": 0.00019865206843807482,
|
| 710 |
+
"loss": 0.49981012344360354,
|
| 711 |
+
"mean_token_accuracy": 0.8560848504304885,
|
| 712 |
+
"num_tokens": 1585718.0,
|
| 713 |
+
"step": 680
|
| 714 |
+
},
|
| 715 |
+
{
|
| 716 |
+
"epoch": 1.692403486924035,
|
| 717 |
+
"eval_entropy": 0.539117265406043,
|
| 718 |
+
"eval_loss": 0.53994220495224,
|
| 719 |
+
"eval_mean_token_accuracy": 0.8488582601380903,
|
| 720 |
+
"eval_num_tokens": 1585718.0,
|
| 721 |
+
"eval_runtime": 86.5296,
|
| 722 |
+
"eval_samples_per_second": 15.902,
|
| 723 |
+
"eval_steps_per_second": 1.988,
|
| 724 |
+
"step": 680
|
| 725 |
+
},
|
| 726 |
+
{
|
| 727 |
+
"entropy": 0.5543891470879316,
|
| 728 |
+
"epoch": 1.7422166874221667,
|
| 729 |
+
"grad_norm": 0.6068442463874817,
|
| 730 |
+
"learning_rate": 0.0001982204261804297,
|
| 731 |
+
"loss": 0.498047399520874,
|
| 732 |
+
"mean_token_accuracy": 0.8554679051041603,
|
| 733 |
+
"num_tokens": 1635718.0,
|
| 734 |
+
"step": 700
|
| 735 |
+
},
|
| 736 |
+
{
|
| 737 |
+
"epoch": 1.7422166874221667,
|
| 738 |
+
"eval_entropy": 0.5703774151760478,
|
| 739 |
+
"eval_loss": 0.5300245881080627,
|
| 740 |
+
"eval_mean_token_accuracy": 0.850798153946566,
|
| 741 |
+
"eval_num_tokens": 1635718.0,
|
| 742 |
+
"eval_runtime": 86.6456,
|
| 743 |
+
"eval_samples_per_second": 15.881,
|
| 744 |
+
"eval_steps_per_second": 1.985,
|
| 745 |
+
"step": 700
|
| 746 |
+
},
|
| 747 |
+
{
|
| 748 |
+
"entropy": 0.546524541825056,
|
| 749 |
+
"epoch": 1.792029887920299,
|
| 750 |
+
"grad_norm": 0.7274155020713806,
|
| 751 |
+
"learning_rate": 0.00019775939618332566,
|
| 752 |
+
"loss": 0.4988589286804199,
|
| 753 |
+
"mean_token_accuracy": 0.853422473371029,
|
| 754 |
+
"num_tokens": 1681291.0,
|
| 755 |
+
"step": 720
|
| 756 |
+
},
|
| 757 |
+
{
|
| 758 |
+
"epoch": 1.792029887920299,
|
| 759 |
+
"eval_entropy": 0.5614905688305234,
|
| 760 |
+
"eval_loss": 0.5350332260131836,
|
| 761 |
+
"eval_mean_token_accuracy": 0.8492204359797544,
|
| 762 |
+
"eval_num_tokens": 1681291.0,
|
| 763 |
+
"eval_runtime": 86.7581,
|
| 764 |
+
"eval_samples_per_second": 15.86,
|
| 765 |
+
"eval_steps_per_second": 1.983,
|
| 766 |
+
"step": 720
|
| 767 |
+
},
|
| 768 |
+
{
|
| 769 |
+
"entropy": 0.5519792139530182,
|
| 770 |
+
"epoch": 1.841843088418431,
|
| 771 |
+
"grad_norm": 0.663466215133667,
|
| 772 |
+
"learning_rate": 0.00019726911748712167,
|
| 773 |
+
"loss": 0.5099314212799072,
|
| 774 |
+
"mean_token_accuracy": 0.848412600159645,
|
| 775 |
+
"num_tokens": 1729102.0,
|
| 776 |
+
"step": 740
|
| 777 |
+
},
|
| 778 |
+
{
|
| 779 |
+
"epoch": 1.841843088418431,
|
| 780 |
+
"eval_entropy": 0.5583519090053647,
|
| 781 |
+
"eval_loss": 0.530483603477478,
|
| 782 |
+
"eval_mean_token_accuracy": 0.8500003374593202,
|
| 783 |
+
"eval_num_tokens": 1729102.0,
|
| 784 |
+
"eval_runtime": 86.3961,
|
| 785 |
+
"eval_samples_per_second": 15.927,
|
| 786 |
+
"eval_steps_per_second": 1.991,
|
| 787 |
+
"step": 740
|
| 788 |
+
},
|
| 789 |
+
{
|
| 790 |
+
"entropy": 0.5454779766499996,
|
| 791 |
+
"epoch": 1.891656288916563,
|
| 792 |
+
"grad_norm": 0.890394926071167,
|
| 793 |
+
"learning_rate": 0.00019674973795318548,
|
| 794 |
+
"loss": 0.4931994915008545,
|
| 795 |
+
"mean_token_accuracy": 0.8540832489728928,
|
| 796 |
+
"num_tokens": 1773578.0,
|
| 797 |
+
"step": 760
|
| 798 |
+
},
|
| 799 |
+
{
|
| 800 |
+
"epoch": 1.891656288916563,
|
| 801 |
+
"eval_entropy": 0.572755502406941,
|
| 802 |
+
"eval_loss": 0.5415747761726379,
|
| 803 |
+
"eval_mean_token_accuracy": 0.8444425803284312,
|
| 804 |
+
"eval_num_tokens": 1773578.0,
|
| 805 |
+
"eval_runtime": 86.4323,
|
| 806 |
+
"eval_samples_per_second": 15.92,
|
| 807 |
+
"eval_steps_per_second": 1.99,
|
| 808 |
+
"step": 760
|
| 809 |
+
},
|
| 810 |
+
{
|
| 811 |
+
"entropy": 0.5392089951783419,
|
| 812 |
+
"epoch": 1.9414694894146949,
|
| 813 |
+
"grad_norm": 0.632411777973175,
|
| 814 |
+
"learning_rate": 0.00019620141421930058,
|
| 815 |
+
"loss": 0.4957888603210449,
|
| 816 |
+
"mean_token_accuracy": 0.8549866065382957,
|
| 817 |
+
"num_tokens": 1821725.0,
|
| 818 |
+
"step": 780
|
| 819 |
+
},
|
| 820 |
+
{
|
| 821 |
+
"epoch": 1.9414694894146949,
|
| 822 |
+
"eval_entropy": 0.540764772961306,
|
| 823 |
+
"eval_loss": 0.5327216386795044,
|
| 824 |
+
"eval_mean_token_accuracy": 0.850631088364956,
|
| 825 |
+
"eval_num_tokens": 1821725.0,
|
| 826 |
+
"eval_runtime": 86.8097,
|
| 827 |
+
"eval_samples_per_second": 15.851,
|
| 828 |
+
"eval_steps_per_second": 1.981,
|
| 829 |
+
"step": 780
|
| 830 |
+
},
|
| 831 |
+
{
|
| 832 |
+
"entropy": 0.5674678739160299,
|
| 833 |
+
"epoch": 1.9912826899128269,
|
| 834 |
+
"grad_norm": 0.6958843469619751,
|
| 835 |
+
"learning_rate": 0.0001956243116524263,
|
| 836 |
+
"loss": 0.504389762878418,
|
| 837 |
+
"mean_token_accuracy": 0.8527948908507824,
|
| 838 |
+
"num_tokens": 1868431.0,
|
| 839 |
+
"step": 800
|
| 840 |
+
},
|
| 841 |
+
{
|
| 842 |
+
"epoch": 1.9912826899128269,
|
| 843 |
+
"eval_entropy": 0.530262403190136,
|
| 844 |
+
"eval_loss": 0.5308871865272522,
|
| 845 |
+
"eval_mean_token_accuracy": 0.8522498046242913,
|
| 846 |
+
"eval_num_tokens": 1868431.0,
|
| 847 |
+
"eval_runtime": 86.7942,
|
| 848 |
+
"eval_samples_per_second": 15.854,
|
| 849 |
+
"eval_steps_per_second": 1.982,
|
| 850 |
+
"step": 800
|
| 851 |
+
},
|
| 852 |
+
{
|
| 853 |
+
"entropy": 0.4742849511213792,
|
| 854 |
+
"epoch": 2.0398505603985058,
|
| 855 |
+
"grad_norm": 0.6941492557525635,
|
| 856 |
+
"learning_rate": 0.00019501860429882556,
|
| 857 |
+
"loss": 0.418599271774292,
|
| 858 |
+
"mean_token_accuracy": 0.8748210859604371,
|
| 859 |
+
"num_tokens": 1915280.0,
|
| 860 |
+
"step": 820
|
| 861 |
+
},
|
| 862 |
+
{
|
| 863 |
+
"epoch": 2.0398505603985058,
|
| 864 |
+
"eval_entropy": 0.504602165069691,
|
| 865 |
+
"eval_loss": 0.542878270149231,
|
| 866 |
+
"eval_mean_token_accuracy": 0.8507604484641275,
|
| 867 |
+
"eval_num_tokens": 1915280.0,
|
| 868 |
+
"eval_runtime": 86.7841,
|
| 869 |
+
"eval_samples_per_second": 15.855,
|
| 870 |
+
"eval_steps_per_second": 1.982,
|
| 871 |
+
"step": 820
|
| 872 |
+
},
|
| 873 |
+
{
|
| 874 |
+
"entropy": 0.45857742577791216,
|
| 875 |
+
"epoch": 2.0896637608966375,
|
| 876 |
+
"grad_norm": 0.5791997909545898,
|
| 877 |
+
"learning_rate": 0.00019438447483157478,
|
| 878 |
+
"loss": 0.399777889251709,
|
| 879 |
+
"mean_token_accuracy": 0.8754058346152306,
|
| 880 |
+
"num_tokens": 1965306.0,
|
| 881 |
+
"step": 840
|
| 882 |
+
},
|
| 883 |
+
{
|
| 884 |
+
"epoch": 2.0896637608966375,
|
| 885 |
+
"eval_entropy": 0.5028848362176918,
|
| 886 |
+
"eval_loss": 0.5356478095054626,
|
| 887 |
+
"eval_mean_token_accuracy": 0.8525635412959165,
|
| 888 |
+
"eval_num_tokens": 1965306.0,
|
| 889 |
+
"eval_runtime": 86.6707,
|
| 890 |
+
"eval_samples_per_second": 15.876,
|
| 891 |
+
"eval_steps_per_second": 1.985,
|
| 892 |
+
"step": 840
|
| 893 |
+
},
|
| 894 |
+
{
|
| 895 |
+
"entropy": 0.4869446292519569,
|
| 896 |
+
"epoch": 2.1394769613947697,
|
| 897 |
+
"grad_norm": 0.6483516693115234,
|
| 898 |
+
"learning_rate": 0.00019372211449547223,
|
| 899 |
+
"loss": 0.40715818405151366,
|
| 900 |
+
"mean_token_accuracy": 0.875113020837307,
|
| 901 |
+
"num_tokens": 2008562.0,
|
| 902 |
+
"step": 860
|
| 903 |
+
},
|
| 904 |
+
{
|
| 905 |
+
"epoch": 2.1394769613947697,
|
| 906 |
+
"eval_entropy": 0.4928991326759028,
|
| 907 |
+
"eval_loss": 0.5419561862945557,
|
| 908 |
+
"eval_mean_token_accuracy": 0.8516040146350861,
|
| 909 |
+
"eval_num_tokens": 2008562.0,
|
| 910 |
+
"eval_runtime": 87.0686,
|
| 911 |
+
"eval_samples_per_second": 15.804,
|
| 912 |
+
"eval_steps_per_second": 1.975,
|
| 913 |
+
"step": 860
|
| 914 |
+
},
|
| 915 |
+
{
|
| 916 |
+
"entropy": 0.45819590501487256,
|
| 917 |
+
"epoch": 2.1892901618929015,
|
| 918 |
+
"grad_norm": 0.6661920547485352,
|
| 919 |
+
"learning_rate": 0.00019303172304936108,
|
| 920 |
+
"loss": 0.39511430263519287,
|
| 921 |
+
"mean_token_accuracy": 0.8780680045485496,
|
| 922 |
+
"num_tokens": 2056474.0,
|
| 923 |
+
"step": 880
|
| 924 |
+
},
|
| 925 |
+
{
|
| 926 |
+
"epoch": 2.1892901618929015,
|
| 927 |
+
"eval_entropy": 0.48602560647698334,
|
| 928 |
+
"eval_loss": 0.5436084866523743,
|
| 929 |
+
"eval_mean_token_accuracy": 0.8500938470973525,
|
| 930 |
+
"eval_num_tokens": 2056474.0,
|
| 931 |
+
"eval_runtime": 86.6809,
|
| 932 |
+
"eval_samples_per_second": 15.874,
|
| 933 |
+
"eval_steps_per_second": 1.984,
|
| 934 |
+
"step": 880
|
| 935 |
+
},
|
| 936 |
+
{
|
| 937 |
+
"entropy": 0.4780638810247183,
|
| 938 |
+
"epoch": 2.2391033623910337,
|
| 939 |
+
"grad_norm": 0.6870484352111816,
|
| 940 |
+
"learning_rate": 0.0001923135087058851,
|
| 941 |
+
"loss": 0.4061615467071533,
|
| 942 |
+
"mean_token_accuracy": 0.8766494184732437,
|
| 943 |
+
"num_tokens": 2103543.0,
|
| 944 |
+
"step": 900
|
| 945 |
+
},
|
| 946 |
+
{
|
| 947 |
+
"epoch": 2.2391033623910337,
|
| 948 |
+
"eval_entropy": 0.48236206035281337,
|
| 949 |
+
"eval_loss": 0.5446090698242188,
|
| 950 |
+
"eval_mean_token_accuracy": 0.8507725513258646,
|
| 951 |
+
"eval_num_tokens": 2103543.0,
|
| 952 |
+
"eval_runtime": 86.7398,
|
| 953 |
+
"eval_samples_per_second": 15.864,
|
| 954 |
+
"eval_steps_per_second": 1.983,
|
| 955 |
+
"step": 900
|
| 956 |
+
},
|
| 957 |
+
{
|
| 958 |
+
"entropy": 0.463029869645834,
|
| 959 |
+
"epoch": 2.2889165628891655,
|
| 960 |
+
"grad_norm": 0.6894590854644775,
|
| 961 |
+
"learning_rate": 0.00019156768806869427,
|
| 962 |
+
"loss": 0.39602413177490237,
|
| 963 |
+
"mean_token_accuracy": 0.876420046389103,
|
| 964 |
+
"num_tokens": 2147861.0,
|
| 965 |
+
"step": 920
|
| 966 |
+
},
|
| 967 |
+
{
|
| 968 |
+
"epoch": 2.2889165628891655,
|
| 969 |
+
"eval_entropy": 0.4904779093556626,
|
| 970 |
+
"eval_loss": 0.5404934287071228,
|
| 971 |
+
"eval_mean_token_accuracy": 0.852238280828609,
|
| 972 |
+
"eval_num_tokens": 2147861.0,
|
| 973 |
+
"eval_runtime": 86.5348,
|
| 974 |
+
"eval_samples_per_second": 15.901,
|
| 975 |
+
"eval_steps_per_second": 1.988,
|
| 976 |
+
"step": 920
|
| 977 |
+
},
|
| 978 |
+
{
|
| 979 |
+
"entropy": 0.4817025110125542,
|
| 980 |
+
"epoch": 2.3387297633872977,
|
| 981 |
+
"grad_norm": 0.7756227254867554,
|
| 982 |
+
"learning_rate": 0.00019079448606712033,
|
| 983 |
+
"loss": 0.4177968502044678,
|
| 984 |
+
"mean_token_accuracy": 0.8712256088852882,
|
| 985 |
+
"num_tokens": 2190561.0,
|
| 986 |
+
"step": 940
|
| 987 |
+
},
|
| 988 |
+
{
|
| 989 |
+
"epoch": 2.3387297633872977,
|
| 990 |
+
"eval_entropy": 0.5153802815218305,
|
| 991 |
+
"eval_loss": 0.5424937605857849,
|
| 992 |
+
"eval_mean_token_accuracy": 0.8506565759348315,
|
| 993 |
+
"eval_num_tokens": 2190561.0,
|
| 994 |
+
"eval_runtime": 86.8973,
|
| 995 |
+
"eval_samples_per_second": 15.835,
|
| 996 |
+
"eval_steps_per_second": 1.979,
|
| 997 |
+
"step": 940
|
| 998 |
+
},
|
| 999 |
+
{
|
| 1000 |
+
"entropy": 0.46456389091908934,
|
| 1001 |
+
"epoch": 2.3885429638854294,
|
| 1002 |
+
"grad_norm": 1.2000319957733154,
|
| 1003 |
+
"learning_rate": 0.00018999413588834105,
|
| 1004 |
+
"loss": 0.4084665775299072,
|
| 1005 |
+
"mean_token_accuracy": 0.8750658087432385,
|
| 1006 |
+
"num_tokens": 2239412.0,
|
| 1007 |
+
"step": 960
|
| 1008 |
+
},
|
| 1009 |
+
{
|
| 1010 |
+
"epoch": 2.3885429638854294,
|
| 1011 |
+
"eval_entropy": 0.4849439303195754,
|
| 1012 |
+
"eval_loss": 0.545662522315979,
|
| 1013 |
+
"eval_mean_token_accuracy": 0.8491013112456299,
|
| 1014 |
+
"eval_num_tokens": 2239412.0,
|
| 1015 |
+
"eval_runtime": 86.9049,
|
| 1016 |
+
"eval_samples_per_second": 15.833,
|
| 1017 |
+
"eval_steps_per_second": 1.979,
|
| 1018 |
+
"step": 960
|
| 1019 |
+
},
|
| 1020 |
+
{
|
| 1021 |
+
"entropy": 0.4857471022754908,
|
| 1022 |
+
"epoch": 2.4383561643835616,
|
| 1023 |
+
"grad_norm": 0.9696341753005981,
|
| 1024 |
+
"learning_rate": 0.0001891668789070541,
|
| 1025 |
+
"loss": 0.4149796962738037,
|
| 1026 |
+
"mean_token_accuracy": 0.8704176343977451,
|
| 1027 |
+
"num_tokens": 2286283.0,
|
| 1028 |
+
"step": 980
|
| 1029 |
+
},
|
| 1030 |
+
{
|
| 1031 |
+
"epoch": 2.4383561643835616,
|
| 1032 |
+
"eval_entropy": 0.4872790058684904,
|
| 1033 |
+
"eval_loss": 0.5412707924842834,
|
| 1034 |
+
"eval_mean_token_accuracy": 0.8509329602468846,
|
| 1035 |
+
"eval_num_tokens": 2286283.0,
|
| 1036 |
+
"eval_runtime": 86.7846,
|
| 1037 |
+
"eval_samples_per_second": 15.855,
|
| 1038 |
+
"eval_steps_per_second": 1.982,
|
| 1039 |
+
"step": 980
|
| 1040 |
+
},
|
| 1041 |
+
{
|
| 1042 |
+
"entropy": 0.4727417893707752,
|
| 1043 |
+
"epoch": 2.488169364881694,
|
| 1044 |
+
"grad_norm": 0.7852500677108765,
|
| 1045 |
+
"learning_rate": 0.0001883129646126818,
|
| 1046 |
+
"loss": 0.4142886161804199,
|
| 1047 |
+
"mean_token_accuracy": 0.8712429471313954,
|
| 1048 |
+
"num_tokens": 2333733.0,
|
| 1049 |
+
"step": 1000
|
| 1050 |
+
},
|
| 1051 |
+
{
|
| 1052 |
+
"epoch": 2.488169364881694,
|
| 1053 |
+
"eval_entropy": 0.5386548059624295,
|
| 1054 |
+
"eval_loss": 0.536101222038269,
|
| 1055 |
+
"eval_mean_token_accuracy": 0.8499491239009902,
|
| 1056 |
+
"eval_num_tokens": 2333733.0,
|
| 1057 |
+
"eval_runtime": 86.9501,
|
| 1058 |
+
"eval_samples_per_second": 15.825,
|
| 1059 |
+
"eval_steps_per_second": 1.978,
|
| 1060 |
+
"step": 1000
|
| 1061 |
+
},
|
| 1062 |
+
{
|
| 1063 |
+
"entropy": 0.4673406321555376,
|
| 1064 |
+
"epoch": 2.5379825653798256,
|
| 1065 |
+
"grad_norm": 0.7133921384811401,
|
| 1066 |
+
"learning_rate": 0.0001874326505341286,
|
| 1067 |
+
"loss": 0.40857529640197754,
|
| 1068 |
+
"mean_token_accuracy": 0.8747925907373428,
|
| 1069 |
+
"num_tokens": 2384270.0,
|
| 1070 |
+
"step": 1020
|
| 1071 |
+
},
|
| 1072 |
+
{
|
| 1073 |
+
"epoch": 2.5379825653798256,
|
| 1074 |
+
"eval_entropy": 0.495788364909416,
|
| 1075 |
+
"eval_loss": 0.5418923497200012,
|
| 1076 |
+
"eval_mean_token_accuracy": 0.851321972040243,
|
| 1077 |
+
"eval_num_tokens": 2384270.0,
|
| 1078 |
+
"eval_runtime": 86.7154,
|
| 1079 |
+
"eval_samples_per_second": 15.868,
|
| 1080 |
+
"eval_steps_per_second": 1.983,
|
| 1081 |
+
"step": 1020
|
| 1082 |
+
},
|
| 1083 |
+
{
|
| 1084 |
+
"entropy": 0.47599745728075504,
|
| 1085 |
+
"epoch": 2.587795765877958,
|
| 1086 |
+
"grad_norm": 0.8202953338623047,
|
| 1087 |
+
"learning_rate": 0.0001865262021621137,
|
| 1088 |
+
"loss": 0.40998234748840334,
|
| 1089 |
+
"mean_token_accuracy": 0.8758242674171924,
|
| 1090 |
+
"num_tokens": 2428036.0,
|
| 1091 |
+
"step": 1040
|
| 1092 |
+
},
|
| 1093 |
+
{
|
| 1094 |
+
"epoch": 2.587795765877958,
|
| 1095 |
+
"eval_entropy": 0.4887966953737791,
|
| 1096 |
+
"eval_loss": 0.5408804416656494,
|
| 1097 |
+
"eval_mean_token_accuracy": 0.8512661065473113,
|
| 1098 |
+
"eval_num_tokens": 2428036.0,
|
| 1099 |
+
"eval_runtime": 86.7869,
|
| 1100 |
+
"eval_samples_per_second": 15.855,
|
| 1101 |
+
"eval_steps_per_second": 1.982,
|
| 1102 |
+
"step": 1040
|
| 1103 |
+
},
|
| 1104 |
+
{
|
| 1105 |
+
"entropy": 0.4824396539479494,
|
| 1106 |
+
"epoch": 2.6376089663760895,
|
| 1107 |
+
"grad_norm": 0.6507360935211182,
|
| 1108 |
+
"learning_rate": 0.00018559389286910275,
|
| 1109 |
+
"loss": 0.4165764808654785,
|
| 1110 |
+
"mean_token_accuracy": 0.8722914069890976,
|
| 1111 |
+
"num_tokens": 2476815.0,
|
| 1112 |
+
"step": 1060
|
| 1113 |
+
},
|
| 1114 |
+
{
|
| 1115 |
+
"epoch": 2.6376089663760895,
|
| 1116 |
+
"eval_entropy": 0.4793398808254752,
|
| 1117 |
+
"eval_loss": 0.5326959490776062,
|
| 1118 |
+
"eval_mean_token_accuracy": 0.8534493650807891,
|
| 1119 |
+
"eval_num_tokens": 2476815.0,
|
| 1120 |
+
"eval_runtime": 86.9559,
|
| 1121 |
+
"eval_samples_per_second": 15.824,
|
| 1122 |
+
"eval_steps_per_second": 1.978,
|
| 1123 |
+
"step": 1060
|
| 1124 |
+
},
|
| 1125 |
+
{
|
| 1126 |
+
"entropy": 0.4605010639876127,
|
| 1127 |
+
"epoch": 2.6874221668742218,
|
| 1128 |
+
"grad_norm": 0.6740535497665405,
|
| 1129 |
+
"learning_rate": 0.00018463600382686253,
|
| 1130 |
+
"loss": 0.4123940944671631,
|
| 1131 |
+
"mean_token_accuracy": 0.8733638986945153,
|
| 1132 |
+
"num_tokens": 2527131.0,
|
| 1133 |
+
"step": 1080
|
| 1134 |
+
},
|
| 1135 |
+
{
|
| 1136 |
+
"epoch": 2.6874221668742218,
|
| 1137 |
+
"eval_entropy": 0.47902208583992584,
|
| 1138 |
+
"eval_loss": 0.5372340083122253,
|
| 1139 |
+
"eval_mean_token_accuracy": 0.851325950303743,
|
| 1140 |
+
"eval_num_tokens": 2527131.0,
|
| 1141 |
+
"eval_runtime": 86.9638,
|
| 1142 |
+
"eval_samples_per_second": 15.823,
|
| 1143 |
+
"eval_steps_per_second": 1.978,
|
| 1144 |
+
"step": 1080
|
| 1145 |
+
},
|
| 1146 |
+
{
|
| 1147 |
+
"entropy": 0.4872019402682781,
|
| 1148 |
+
"epoch": 2.7372353673723535,
|
| 1149 |
+
"grad_norm": 0.6994742155075073,
|
| 1150 |
+
"learning_rate": 0.0001836528239216632,
|
| 1151 |
+
"loss": 0.41599602699279786,
|
| 1152 |
+
"mean_token_accuracy": 0.872775862365961,
|
| 1153 |
+
"num_tokens": 2572537.0,
|
| 1154 |
+
"step": 1100
|
| 1155 |
+
},
|
| 1156 |
+
{
|
| 1157 |
+
"epoch": 2.7372353673723535,
|
| 1158 |
+
"eval_entropy": 0.4893243626453156,
|
| 1159 |
+
"eval_loss": 0.5327795743942261,
|
| 1160 |
+
"eval_mean_token_accuracy": 0.8537560302850812,
|
| 1161 |
+
"eval_num_tokens": 2572537.0,
|
| 1162 |
+
"eval_runtime": 86.823,
|
| 1163 |
+
"eval_samples_per_second": 15.848,
|
| 1164 |
+
"eval_steps_per_second": 1.981,
|
| 1165 |
+
"step": 1100
|
| 1166 |
+
},
|
| 1167 |
+
{
|
| 1168 |
+
"entropy": 0.4949610233306885,
|
| 1169 |
+
"epoch": 2.7870485678704857,
|
| 1170 |
+
"grad_norm": 0.9605912566184998,
|
| 1171 |
+
"learning_rate": 0.0001826446496671543,
|
| 1172 |
+
"loss": 0.4266993045806885,
|
| 1173 |
+
"mean_token_accuracy": 0.8688005246222019,
|
| 1174 |
+
"num_tokens": 2616047.0,
|
| 1175 |
+
"step": 1120
|
| 1176 |
+
},
|
| 1177 |
+
{
|
| 1178 |
+
"epoch": 2.7870485678704857,
|
| 1179 |
+
"eval_entropy": 0.5061517927882283,
|
| 1180 |
+
"eval_loss": 0.5356810092926025,
|
| 1181 |
+
"eval_mean_token_accuracy": 0.8524593568818514,
|
| 1182 |
+
"eval_num_tokens": 2616047.0,
|
| 1183 |
+
"eval_runtime": 86.8385,
|
| 1184 |
+
"eval_samples_per_second": 15.846,
|
| 1185 |
+
"eval_steps_per_second": 1.981,
|
| 1186 |
+
"step": 1120
|
| 1187 |
+
}
|
| 1188 |
+
],
|
| 1189 |
+
"logging_steps": 20,
|
| 1190 |
+
"max_steps": 4020,
|
| 1191 |
+
"num_input_tokens_seen": 0,
|
| 1192 |
+
"num_train_epochs": 10,
|
| 1193 |
+
"save_steps": 20,
|
| 1194 |
+
"stateful_callbacks": {
|
| 1195 |
+
"TrainerControl": {
|
| 1196 |
+
"args": {
|
| 1197 |
+
"should_epoch_stop": false,
|
| 1198 |
+
"should_evaluate": false,
|
| 1199 |
+
"should_log": false,
|
| 1200 |
+
"should_save": true,
|
| 1201 |
+
"should_training_stop": false
|
| 1202 |
+
},
|
| 1203 |
+
"attributes": {}
|
| 1204 |
+
}
|
| 1205 |
+
},
|
| 1206 |
+
"total_flos": 1.1058529480242586e+17,
|
| 1207 |
+
"train_batch_size": 4,
|
| 1208 |
+
"trial_name": null,
|
| 1209 |
+
"trial_params": null
|
| 1210 |
+
}
|
overgeneralisation_original_Swedish/Qwen3.5-4B-Base_overgeneralisation_splits_original_features_train_overgeneralisation_splits_original_features_test1/checkpoint-1140/README.md
ADDED
|
@@ -0,0 +1,209 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
---
|
| 2 |
+
base_model: Qwen/Qwen3.5-4B-Base
|
| 3 |
+
library_name: peft
|
| 4 |
+
pipeline_tag: text-generation
|
| 5 |
+
tags:
|
| 6 |
+
- base_model:adapter:Qwen/Qwen3.5-4B-Base
|
| 7 |
+
- lora
|
| 8 |
+
- sft
|
| 9 |
+
- transformers
|
| 10 |
+
- trl
|
| 11 |
+
---
|
| 12 |
+
|
| 13 |
+
# Model Card for Model ID
|
| 14 |
+
|
| 15 |
+
<!-- Provide a quick summary of what the model is/does. -->
|
| 16 |
+
|
| 17 |
+
|
| 18 |
+
|
| 19 |
+
## Model Details
|
| 20 |
+
|
| 21 |
+
### Model Description
|
| 22 |
+
|
| 23 |
+
<!-- Provide a longer summary of what this model is. -->
|
| 24 |
+
|
| 25 |
+
|
| 26 |
+
|
| 27 |
+
- **Developed by:** [More Information Needed]
|
| 28 |
+
- **Funded by [optional]:** [More Information Needed]
|
| 29 |
+
- **Shared by [optional]:** [More Information Needed]
|
| 30 |
+
- **Model type:** [More Information Needed]
|
| 31 |
+
- **Language(s) (NLP):** [More Information Needed]
|
| 32 |
+
- **License:** [More Information Needed]
|
| 33 |
+
- **Finetuned from model [optional]:** [More Information Needed]
|
| 34 |
+
|
| 35 |
+
### Model Sources [optional]
|
| 36 |
+
|
| 37 |
+
<!-- Provide the basic links for the model. -->
|
| 38 |
+
|
| 39 |
+
- **Repository:** [More Information Needed]
|
| 40 |
+
- **Paper [optional]:** [More Information Needed]
|
| 41 |
+
- **Demo [optional]:** [More Information Needed]
|
| 42 |
+
|
| 43 |
+
## Uses
|
| 44 |
+
|
| 45 |
+
<!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
|
| 46 |
+
|
| 47 |
+
### Direct Use
|
| 48 |
+
|
| 49 |
+
<!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
|
| 50 |
+
|
| 51 |
+
[More Information Needed]
|
| 52 |
+
|
| 53 |
+
### Downstream Use [optional]
|
| 54 |
+
|
| 55 |
+
<!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
|
| 56 |
+
|
| 57 |
+
[More Information Needed]
|
| 58 |
+
|
| 59 |
+
### Out-of-Scope Use
|
| 60 |
+
|
| 61 |
+
<!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
|
| 62 |
+
|
| 63 |
+
[More Information Needed]
|
| 64 |
+
|
| 65 |
+
## Bias, Risks, and Limitations
|
| 66 |
+
|
| 67 |
+
<!-- This section is meant to convey both technical and sociotechnical limitations. -->
|
| 68 |
+
|
| 69 |
+
[More Information Needed]
|
| 70 |
+
|
| 71 |
+
### Recommendations
|
| 72 |
+
|
| 73 |
+
<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
|
| 74 |
+
|
| 75 |
+
Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
|
| 76 |
+
|
| 77 |
+
## How to Get Started with the Model
|
| 78 |
+
|
| 79 |
+
Use the code below to get started with the model.
|
| 80 |
+
|
| 81 |
+
[More Information Needed]
|
| 82 |
+
|
| 83 |
+
## Training Details
|
| 84 |
+
|
| 85 |
+
### Training Data
|
| 86 |
+
|
| 87 |
+
<!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
|
| 88 |
+
|
| 89 |
+
[More Information Needed]
|
| 90 |
+
|
| 91 |
+
### Training Procedure
|
| 92 |
+
|
| 93 |
+
<!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
|
| 94 |
+
|
| 95 |
+
#### Preprocessing [optional]
|
| 96 |
+
|
| 97 |
+
[More Information Needed]
|
| 98 |
+
|
| 99 |
+
|
| 100 |
+
#### Training Hyperparameters
|
| 101 |
+
|
| 102 |
+
- **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
|
| 103 |
+
|
| 104 |
+
#### Speeds, Sizes, Times [optional]
|
| 105 |
+
|
| 106 |
+
<!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
|
| 107 |
+
|
| 108 |
+
[More Information Needed]
|
| 109 |
+
|
| 110 |
+
## Evaluation
|
| 111 |
+
|
| 112 |
+
<!-- This section describes the evaluation protocols and provides the results. -->
|
| 113 |
+
|
| 114 |
+
### Testing Data, Factors & Metrics
|
| 115 |
+
|
| 116 |
+
#### Testing Data
|
| 117 |
+
|
| 118 |
+
<!-- This should link to a Dataset Card if possible. -->
|
| 119 |
+
|
| 120 |
+
[More Information Needed]
|
| 121 |
+
|
| 122 |
+
#### Factors
|
| 123 |
+
|
| 124 |
+
<!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
|
| 125 |
+
|
| 126 |
+
[More Information Needed]
|
| 127 |
+
|
| 128 |
+
#### Metrics
|
| 129 |
+
|
| 130 |
+
<!-- These are the evaluation metrics being used, ideally with a description of why. -->
|
| 131 |
+
|
| 132 |
+
[More Information Needed]
|
| 133 |
+
|
| 134 |
+
### Results
|
| 135 |
+
|
| 136 |
+
[More Information Needed]
|
| 137 |
+
|
| 138 |
+
#### Summary
|
| 139 |
+
|
| 140 |
+
|
| 141 |
+
|
| 142 |
+
## Model Examination [optional]
|
| 143 |
+
|
| 144 |
+
<!-- Relevant interpretability work for the model goes here -->
|
| 145 |
+
|
| 146 |
+
[More Information Needed]
|
| 147 |
+
|
| 148 |
+
## Environmental Impact
|
| 149 |
+
|
| 150 |
+
<!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
|
| 151 |
+
|
| 152 |
+
Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
|
| 153 |
+
|
| 154 |
+
- **Hardware Type:** [More Information Needed]
|
| 155 |
+
- **Hours used:** [More Information Needed]
|
| 156 |
+
- **Cloud Provider:** [More Information Needed]
|
| 157 |
+
- **Compute Region:** [More Information Needed]
|
| 158 |
+
- **Carbon Emitted:** [More Information Needed]
|
| 159 |
+
|
| 160 |
+
## Technical Specifications [optional]
|
| 161 |
+
|
| 162 |
+
### Model Architecture and Objective
|
| 163 |
+
|
| 164 |
+
[More Information Needed]
|
| 165 |
+
|
| 166 |
+
### Compute Infrastructure
|
| 167 |
+
|
| 168 |
+
[More Information Needed]
|
| 169 |
+
|
| 170 |
+
#### Hardware
|
| 171 |
+
|
| 172 |
+
[More Information Needed]
|
| 173 |
+
|
| 174 |
+
#### Software
|
| 175 |
+
|
| 176 |
+
[More Information Needed]
|
| 177 |
+
|
| 178 |
+
## Citation [optional]
|
| 179 |
+
|
| 180 |
+
<!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
|
| 181 |
+
|
| 182 |
+
**BibTeX:**
|
| 183 |
+
|
| 184 |
+
[More Information Needed]
|
| 185 |
+
|
| 186 |
+
**APA:**
|
| 187 |
+
|
| 188 |
+
[More Information Needed]
|
| 189 |
+
|
| 190 |
+
## Glossary [optional]
|
| 191 |
+
|
| 192 |
+
<!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
|
| 193 |
+
|
| 194 |
+
[More Information Needed]
|
| 195 |
+
|
| 196 |
+
## More Information [optional]
|
| 197 |
+
|
| 198 |
+
[More Information Needed]
|
| 199 |
+
|
| 200 |
+
## Model Card Authors [optional]
|
| 201 |
+
|
| 202 |
+
[More Information Needed]
|
| 203 |
+
|
| 204 |
+
## Model Card Contact
|
| 205 |
+
|
| 206 |
+
[More Information Needed]
|
| 207 |
+
### Framework versions
|
| 208 |
+
|
| 209 |
+
- PEFT 0.18.1
|
overgeneralisation_original_Swedish/Qwen3.5-4B-Base_overgeneralisation_splits_original_features_train_overgeneralisation_splits_original_features_test1/checkpoint-1140/adapter_config.json
ADDED
|
@@ -0,0 +1,46 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
{
|
| 2 |
+
"alora_invocation_tokens": null,
|
| 3 |
+
"alpha_pattern": {},
|
| 4 |
+
"arrow_config": null,
|
| 5 |
+
"auto_mapping": null,
|
| 6 |
+
"base_model_name_or_path": "Qwen/Qwen3.5-4B-Base",
|
| 7 |
+
"bias": "none",
|
| 8 |
+
"corda_config": null,
|
| 9 |
+
"ensure_weight_tying": false,
|
| 10 |
+
"eva_config": null,
|
| 11 |
+
"exclude_modules": null,
|
| 12 |
+
"fan_in_fan_out": false,
|
| 13 |
+
"inference_mode": true,
|
| 14 |
+
"init_lora_weights": true,
|
| 15 |
+
"layer_replication": null,
|
| 16 |
+
"layers_pattern": null,
|
| 17 |
+
"layers_to_transform": null,
|
| 18 |
+
"loftq_config": {},
|
| 19 |
+
"lora_alpha": 256,
|
| 20 |
+
"lora_bias": false,
|
| 21 |
+
"lora_dropout": 0.0005183818805460705,
|
| 22 |
+
"megatron_config": null,
|
| 23 |
+
"megatron_core": "megatron.core",
|
| 24 |
+
"modules_to_save": null,
|
| 25 |
+
"peft_type": "LORA",
|
| 26 |
+
"peft_version": "0.18.1",
|
| 27 |
+
"qalora_group_size": 16,
|
| 28 |
+
"r": 128,
|
| 29 |
+
"rank_pattern": {},
|
| 30 |
+
"revision": null,
|
| 31 |
+
"target_modules": [
|
| 32 |
+
"up_proj",
|
| 33 |
+
"q_proj",
|
| 34 |
+
"o_proj",
|
| 35 |
+
"v_proj",
|
| 36 |
+
"k_proj",
|
| 37 |
+
"gate_proj",
|
| 38 |
+
"down_proj"
|
| 39 |
+
],
|
| 40 |
+
"target_parameters": null,
|
| 41 |
+
"task_type": "CAUSAL_LM",
|
| 42 |
+
"trainable_token_indices": null,
|
| 43 |
+
"use_dora": false,
|
| 44 |
+
"use_qalora": false,
|
| 45 |
+
"use_rslora": false
|
| 46 |
+
}
|
overgeneralisation_original_Swedish/Qwen3.5-4B-Base_overgeneralisation_splits_original_features_train_overgeneralisation_splits_original_features_test1/checkpoint-1140/chat_template.jinja
ADDED
|
@@ -0,0 +1,154 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
{%- set image_count = namespace(value=0) %}
|
| 2 |
+
{%- set video_count = namespace(value=0) %}
|
| 3 |
+
{%- macro render_content(content, do_vision_count, is_system_content=false) %}
|
| 4 |
+
{%- if content is string %}
|
| 5 |
+
{{- content }}
|
| 6 |
+
{%- elif content is iterable and content is not mapping %}
|
| 7 |
+
{%- for item in content %}
|
| 8 |
+
{%- if 'image' in item or 'image_url' in item or item.type == 'image' %}
|
| 9 |
+
{%- if is_system_content %}
|
| 10 |
+
{{- raise_exception('System message cannot contain images.') }}
|
| 11 |
+
{%- endif %}
|
| 12 |
+
{%- if do_vision_count %}
|
| 13 |
+
{%- set image_count.value = image_count.value + 1 %}
|
| 14 |
+
{%- endif %}
|
| 15 |
+
{%- if add_vision_id %}
|
| 16 |
+
{{- 'Picture ' ~ image_count.value ~ ': ' }}
|
| 17 |
+
{%- endif %}
|
| 18 |
+
{{- '<|vision_start|><|image_pad|><|vision_end|>' }}
|
| 19 |
+
{%- elif 'video' in item or item.type == 'video' %}
|
| 20 |
+
{%- if is_system_content %}
|
| 21 |
+
{{- raise_exception('System message cannot contain videos.') }}
|
| 22 |
+
{%- endif %}
|
| 23 |
+
{%- if do_vision_count %}
|
| 24 |
+
{%- set video_count.value = video_count.value + 1 %}
|
| 25 |
+
{%- endif %}
|
| 26 |
+
{%- if add_vision_id %}
|
| 27 |
+
{{- 'Video ' ~ video_count.value ~ ': ' }}
|
| 28 |
+
{%- endif %}
|
| 29 |
+
{{- '<|vision_start|><|video_pad|><|vision_end|>' }}
|
| 30 |
+
{%- elif 'text' in item %}
|
| 31 |
+
{{- item.text }}
|
| 32 |
+
{%- else %}
|
| 33 |
+
{{- raise_exception('Unexpected item type in content.') }}
|
| 34 |
+
{%- endif %}
|
| 35 |
+
{%- endfor %}
|
| 36 |
+
{%- elif content is none or content is undefined %}
|
| 37 |
+
{{- '' }}
|
| 38 |
+
{%- else %}
|
| 39 |
+
{{- raise_exception('Unexpected content type.') }}
|
| 40 |
+
{%- endif %}
|
| 41 |
+
{%- endmacro %}
|
| 42 |
+
{%- if not messages %}
|
| 43 |
+
{{- raise_exception('No messages provided.') }}
|
| 44 |
+
{%- endif %}
|
| 45 |
+
{%- if tools and tools is iterable and tools is not mapping %}
|
| 46 |
+
{{- '<|im_start|>system\n' }}
|
| 47 |
+
{{- "# Tools\n\nYou have access to the following functions:\n\n<tools>" }}
|
| 48 |
+
{%- for tool in tools %}
|
| 49 |
+
{{- "\n" }}
|
| 50 |
+
{{- tool | tojson }}
|
| 51 |
+
{%- endfor %}
|
| 52 |
+
{{- "\n</tools>" }}
|
| 53 |
+
{{- '\n\nIf you choose to call a function ONLY reply in the following format with NO suffix:\n\n<tool_call>\n<function=example_function_name>\n<parameter=example_parameter_1>\nvalue_1\n</parameter>\n<parameter=example_parameter_2>\nThis is the value for the second parameter\nthat can span\nmultiple lines\n</parameter>\n</function>\n</tool_call>\n\n<IMPORTANT>\nReminder:\n- Function calls MUST follow the specified format: an inner <function=...></function> block must be nested within <tool_call></tool_call> XML tags\n- Required parameters MUST be specified\n- You may provide optional reasoning for your function call in natural language BEFORE the function call, but NOT after\n- If there is no function call available, answer the question like normal with your current knowledge and do not tell the user about function calls\n</IMPORTANT>' }}
|
| 54 |
+
{%- if messages[0].role == 'system' %}
|
| 55 |
+
{%- set content = render_content(messages[0].content, false, true)|trim %}
|
| 56 |
+
{%- if content %}
|
| 57 |
+
{{- '\n\n' + content }}
|
| 58 |
+
{%- endif %}
|
| 59 |
+
{%- endif %}
|
| 60 |
+
{{- '<|im_end|>\n' }}
|
| 61 |
+
{%- else %}
|
| 62 |
+
{%- if messages[0].role == 'system' %}
|
| 63 |
+
{%- set content = render_content(messages[0].content, false, true)|trim %}
|
| 64 |
+
{{- '<|im_start|>system\n' + content + '<|im_end|>\n' }}
|
| 65 |
+
{%- endif %}
|
| 66 |
+
{%- endif %}
|
| 67 |
+
{%- set ns = namespace(multi_step_tool=true, last_query_index=messages|length - 1) %}
|
| 68 |
+
{%- for message in messages[::-1] %}
|
| 69 |
+
{%- set index = (messages|length - 1) - loop.index0 %}
|
| 70 |
+
{%- if ns.multi_step_tool and message.role == "user" %}
|
| 71 |
+
{%- set content = render_content(message.content, false)|trim %}
|
| 72 |
+
{%- if not(content.startswith('<tool_response>') and content.endswith('</tool_response>')) %}
|
| 73 |
+
{%- set ns.multi_step_tool = false %}
|
| 74 |
+
{%- set ns.last_query_index = index %}
|
| 75 |
+
{%- endif %}
|
| 76 |
+
{%- endif %}
|
| 77 |
+
{%- endfor %}
|
| 78 |
+
{%- if ns.multi_step_tool %}
|
| 79 |
+
{{- raise_exception('No user query found in messages.') }}
|
| 80 |
+
{%- endif %}
|
| 81 |
+
{%- for message in messages %}
|
| 82 |
+
{%- set content = render_content(message.content, true)|trim %}
|
| 83 |
+
{%- if message.role == "system" %}
|
| 84 |
+
{%- if not loop.first %}
|
| 85 |
+
{{- raise_exception('System message must be at the beginning.') }}
|
| 86 |
+
{%- endif %}
|
| 87 |
+
{%- elif message.role == "user" %}
|
| 88 |
+
{{- '<|im_start|>' + message.role + '\n' + content + '<|im_end|>' + '\n' }}
|
| 89 |
+
{%- elif message.role == "assistant" %}
|
| 90 |
+
{%- set reasoning_content = '' %}
|
| 91 |
+
{%- if message.reasoning_content is string %}
|
| 92 |
+
{%- set reasoning_content = message.reasoning_content %}
|
| 93 |
+
{%- else %}
|
| 94 |
+
{%- if '</think>' in content %}
|
| 95 |
+
{%- set reasoning_content = content.split('</think>')[0].rstrip('\n').split('<think>')[-1].lstrip('\n') %}
|
| 96 |
+
{%- set content = content.split('</think>')[-1].lstrip('\n') %}
|
| 97 |
+
{%- endif %}
|
| 98 |
+
{%- endif %}
|
| 99 |
+
{%- set reasoning_content = reasoning_content|trim %}
|
| 100 |
+
{%- if loop.index0 > ns.last_query_index %}
|
| 101 |
+
{{- '<|im_start|>' + message.role + '\n<think>\n' + reasoning_content + '\n</think>\n\n' + content }}
|
| 102 |
+
{%- else %}
|
| 103 |
+
{{- '<|im_start|>' + message.role + '\n' + content }}
|
| 104 |
+
{%- endif %}
|
| 105 |
+
{%- if message.tool_calls and message.tool_calls is iterable and message.tool_calls is not mapping %}
|
| 106 |
+
{%- for tool_call in message.tool_calls %}
|
| 107 |
+
{%- if tool_call.function is defined %}
|
| 108 |
+
{%- set tool_call = tool_call.function %}
|
| 109 |
+
{%- endif %}
|
| 110 |
+
{%- if loop.first %}
|
| 111 |
+
{%- if content|trim %}
|
| 112 |
+
{{- '\n\n<tool_call>\n<function=' + tool_call.name + '>\n' }}
|
| 113 |
+
{%- else %}
|
| 114 |
+
{{- '<tool_call>\n<function=' + tool_call.name + '>\n' }}
|
| 115 |
+
{%- endif %}
|
| 116 |
+
{%- else %}
|
| 117 |
+
{{- '\n<tool_call>\n<function=' + tool_call.name + '>\n' }}
|
| 118 |
+
{%- endif %}
|
| 119 |
+
{%- if tool_call.arguments is defined %}
|
| 120 |
+
{%- for args_name, args_value in tool_call.arguments|items %}
|
| 121 |
+
{{- '<parameter=' + args_name + '>\n' }}
|
| 122 |
+
{%- set args_value = args_value | tojson | safe if args_value is mapping or (args_value is sequence and args_value is not string) else args_value | string %}
|
| 123 |
+
{{- args_value }}
|
| 124 |
+
{{- '\n</parameter>\n' }}
|
| 125 |
+
{%- endfor %}
|
| 126 |
+
{%- endif %}
|
| 127 |
+
{{- '</function>\n</tool_call>' }}
|
| 128 |
+
{%- endfor %}
|
| 129 |
+
{%- endif %}
|
| 130 |
+
{{- '<|im_end|>\n' }}
|
| 131 |
+
{%- elif message.role == "tool" %}
|
| 132 |
+
{%- if loop.previtem and loop.previtem.role != "tool" %}
|
| 133 |
+
{{- '<|im_start|>user' }}
|
| 134 |
+
{%- endif %}
|
| 135 |
+
{{- '\n<tool_response>\n' }}
|
| 136 |
+
{{- content }}
|
| 137 |
+
{{- '\n</tool_response>' }}
|
| 138 |
+
{%- if not loop.last and loop.nextitem.role != "tool" %}
|
| 139 |
+
{{- '<|im_end|>\n' }}
|
| 140 |
+
{%- elif loop.last %}
|
| 141 |
+
{{- '<|im_end|>\n' }}
|
| 142 |
+
{%- endif %}
|
| 143 |
+
{%- else %}
|
| 144 |
+
{{- raise_exception('Unexpected message role.') }}
|
| 145 |
+
{%- endif %}
|
| 146 |
+
{%- endfor %}
|
| 147 |
+
{%- if add_generation_prompt %}
|
| 148 |
+
{{- '<|im_start|>assistant\n' }}
|
| 149 |
+
{%- if enable_thinking is defined and enable_thinking is false %}
|
| 150 |
+
{{- '<think>\n\n</think>\n\n' }}
|
| 151 |
+
{%- else %}
|
| 152 |
+
{{- '<think>\n' }}
|
| 153 |
+
{%- endif %}
|
| 154 |
+
{%- endif %}
|
overgeneralisation_original_Swedish/Qwen3.5-4B-Base_overgeneralisation_splits_original_features_train_overgeneralisation_splits_original_features_test1/checkpoint-1140/tokenizer_config.json
ADDED
|
@@ -0,0 +1,31 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
{
|
| 2 |
+
"add_prefix_space": false,
|
| 3 |
+
"audio_bos_token": "<|audio_start|>",
|
| 4 |
+
"audio_eos_token": "<|audio_end|>",
|
| 5 |
+
"audio_token": "<|audio_pad|>",
|
| 6 |
+
"backend": "tokenizers",
|
| 7 |
+
"bos_token": null,
|
| 8 |
+
"clean_up_tokenization_spaces": false,
|
| 9 |
+
"eos_token": "<|endoftext|>",
|
| 10 |
+
"errors": "replace",
|
| 11 |
+
"image_token": "<|image_pad|>",
|
| 12 |
+
"is_local": false,
|
| 13 |
+
"model_max_length": 262144,
|
| 14 |
+
"model_specific_special_tokens": {
|
| 15 |
+
"audio_bos_token": "<|audio_start|>",
|
| 16 |
+
"audio_eos_token": "<|audio_end|>",
|
| 17 |
+
"audio_token": "<|audio_pad|>",
|
| 18 |
+
"image_token": "<|image_pad|>",
|
| 19 |
+
"video_token": "<|video_pad|>",
|
| 20 |
+
"vision_bos_token": "<|vision_start|>",
|
| 21 |
+
"vision_eos_token": "<|vision_end|>"
|
| 22 |
+
},
|
| 23 |
+
"pad_token": "<|endoftext|>",
|
| 24 |
+
"pretokenize_regex": "(?i:'s|'t|'re|'ve|'m|'ll|'d)|[^\\r\\n\\p{L}\\p{N}]?[\\p{L}\\p{M}]+|\\p{N}| ?[^\\s\\p{L}\\p{M}\\p{N}]+[\\r\\n]*|\\s*[\\r\\n]+|\\s+(?!\\S)|\\s+",
|
| 25 |
+
"split_special_tokens": false,
|
| 26 |
+
"tokenizer_class": "TokenizersBackend",
|
| 27 |
+
"unk_token": null,
|
| 28 |
+
"video_token": "<|video_pad|>",
|
| 29 |
+
"vision_bos_token": "<|vision_start|>",
|
| 30 |
+
"vision_eos_token": "<|vision_end|>"
|
| 31 |
+
}
|
overgeneralisation_original_Swedish/Qwen3.5-4B-Base_overgeneralisation_splits_original_features_train_overgeneralisation_splits_original_features_test1/checkpoint-1140/trainer_state.json
ADDED
|
@@ -0,0 +1,1231 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
{
|
| 2 |
+
"best_global_step": null,
|
| 3 |
+
"best_metric": null,
|
| 4 |
+
"best_model_checkpoint": null,
|
| 5 |
+
"epoch": 2.8368617683686175,
|
| 6 |
+
"eval_steps": 20,
|
| 7 |
+
"global_step": 1140,
|
| 8 |
+
"is_hyper_param_search": false,
|
| 9 |
+
"is_local_process_zero": true,
|
| 10 |
+
"is_world_process_zero": true,
|
| 11 |
+
"log_history": [
|
| 12 |
+
{
|
| 13 |
+
"entropy": 1.9784346982836722,
|
| 14 |
+
"epoch": 0.049813200498132,
|
| 15 |
+
"grad_norm": 3.0229668617248535,
|
| 16 |
+
"learning_rate": 9.526142962415369e-06,
|
| 17 |
+
"loss": 1.7360023498535155,
|
| 18 |
+
"mean_token_accuracy": 0.6449888605624438,
|
| 19 |
+
"num_tokens": 46794.0,
|
| 20 |
+
"step": 20
|
| 21 |
+
},
|
| 22 |
+
{
|
| 23 |
+
"epoch": 0.049813200498132,
|
| 24 |
+
"eval_entropy": 1.41506897571475,
|
| 25 |
+
"eval_loss": 1.1876318454742432,
|
| 26 |
+
"eval_mean_token_accuracy": 0.734131895525511,
|
| 27 |
+
"eval_num_tokens": 46794.0,
|
| 28 |
+
"eval_runtime": 87.8071,
|
| 29 |
+
"eval_samples_per_second": 15.671,
|
| 30 |
+
"eval_steps_per_second": 1.959,
|
| 31 |
+
"step": 20
|
| 32 |
+
},
|
| 33 |
+
{
|
| 34 |
+
"entropy": 1.049924298375845,
|
| 35 |
+
"epoch": 0.099626400996264,
|
| 36 |
+
"grad_norm": 1.5795097351074219,
|
| 37 |
+
"learning_rate": 1.9553661870221022e-05,
|
| 38 |
+
"loss": 0.8944448471069336,
|
| 39 |
+
"mean_token_accuracy": 0.7748479396104813,
|
| 40 |
+
"num_tokens": 90754.0,
|
| 41 |
+
"step": 40
|
| 42 |
+
},
|
| 43 |
+
{
|
| 44 |
+
"epoch": 0.099626400996264,
|
| 45 |
+
"eval_entropy": 0.7996658658565476,
|
| 46 |
+
"eval_loss": 0.7202735543251038,
|
| 47 |
+
"eval_mean_token_accuracy": 0.8070558306089667,
|
| 48 |
+
"eval_num_tokens": 90754.0,
|
| 49 |
+
"eval_runtime": 86.9199,
|
| 50 |
+
"eval_samples_per_second": 15.831,
|
| 51 |
+
"eval_steps_per_second": 1.979,
|
| 52 |
+
"step": 40
|
| 53 |
+
},
|
| 54 |
+
{
|
| 55 |
+
"entropy": 0.7734908878803253,
|
| 56 |
+
"epoch": 0.149439601494396,
|
| 57 |
+
"grad_norm": 1.3136248588562012,
|
| 58 |
+
"learning_rate": 2.9581180778026673e-05,
|
| 59 |
+
"loss": 0.6780608654022217,
|
| 60 |
+
"mean_token_accuracy": 0.8168170280754566,
|
| 61 |
+
"num_tokens": 137472.0,
|
| 62 |
+
"step": 60
|
| 63 |
+
},
|
| 64 |
+
{
|
| 65 |
+
"epoch": 0.149439601494396,
|
| 66 |
+
"eval_entropy": 0.7119324009778888,
|
| 67 |
+
"eval_loss": 0.6554311513900757,
|
| 68 |
+
"eval_mean_token_accuracy": 0.8215604798738346,
|
| 69 |
+
"eval_num_tokens": 137472.0,
|
| 70 |
+
"eval_runtime": 86.8692,
|
| 71 |
+
"eval_samples_per_second": 15.84,
|
| 72 |
+
"eval_steps_per_second": 1.98,
|
| 73 |
+
"step": 60
|
| 74 |
+
},
|
| 75 |
+
{
|
| 76 |
+
"entropy": 0.7071127541363239,
|
| 77 |
+
"epoch": 0.199252801992528,
|
| 78 |
+
"grad_norm": 1.387060284614563,
|
| 79 |
+
"learning_rate": 3.960869968583232e-05,
|
| 80 |
+
"loss": 0.6382100582122803,
|
| 81 |
+
"mean_token_accuracy": 0.8229366384446621,
|
| 82 |
+
"num_tokens": 187408.0,
|
| 83 |
+
"step": 80
|
| 84 |
+
},
|
| 85 |
+
{
|
| 86 |
+
"epoch": 0.199252801992528,
|
| 87 |
+
"eval_entropy": 0.6883931482254073,
|
| 88 |
+
"eval_loss": 0.625065803527832,
|
| 89 |
+
"eval_mean_token_accuracy": 0.828940509710201,
|
| 90 |
+
"eval_num_tokens": 187408.0,
|
| 91 |
+
"eval_runtime": 86.662,
|
| 92 |
+
"eval_samples_per_second": 15.878,
|
| 93 |
+
"eval_steps_per_second": 1.985,
|
| 94 |
+
"step": 80
|
| 95 |
+
},
|
| 96 |
+
{
|
| 97 |
+
"entropy": 0.6800824083387852,
|
| 98 |
+
"epoch": 0.24906600249066002,
|
| 99 |
+
"grad_norm": 0.9892916679382324,
|
| 100 |
+
"learning_rate": 4.963621859363797e-05,
|
| 101 |
+
"loss": 0.6011715888977051,
|
| 102 |
+
"mean_token_accuracy": 0.8323964163661003,
|
| 103 |
+
"num_tokens": 234197.0,
|
| 104 |
+
"step": 100
|
| 105 |
+
},
|
| 106 |
+
{
|
| 107 |
+
"epoch": 0.24906600249066002,
|
| 108 |
+
"eval_entropy": 0.6840810470802839,
|
| 109 |
+
"eval_loss": 0.6037028431892395,
|
| 110 |
+
"eval_mean_token_accuracy": 0.8309669033732525,
|
| 111 |
+
"eval_num_tokens": 234197.0,
|
| 112 |
+
"eval_runtime": 86.4637,
|
| 113 |
+
"eval_samples_per_second": 15.914,
|
| 114 |
+
"eval_steps_per_second": 1.989,
|
| 115 |
+
"step": 100
|
| 116 |
+
},
|
| 117 |
+
{
|
| 118 |
+
"entropy": 0.6776216626167297,
|
| 119 |
+
"epoch": 0.298879202988792,
|
| 120 |
+
"grad_norm": 0.8918434977531433,
|
| 121 |
+
"learning_rate": 5.9663737501443624e-05,
|
| 122 |
+
"loss": 0.5991742610931396,
|
| 123 |
+
"mean_token_accuracy": 0.8300838828086853,
|
| 124 |
+
"num_tokens": 281241.0,
|
| 125 |
+
"step": 120
|
| 126 |
+
},
|
| 127 |
+
{
|
| 128 |
+
"epoch": 0.298879202988792,
|
| 129 |
+
"eval_entropy": 0.690427724705186,
|
| 130 |
+
"eval_loss": 0.5939701795578003,
|
| 131 |
+
"eval_mean_token_accuracy": 0.8345950186945671,
|
| 132 |
+
"eval_num_tokens": 281241.0,
|
| 133 |
+
"eval_runtime": 86.6626,
|
| 134 |
+
"eval_samples_per_second": 15.878,
|
| 135 |
+
"eval_steps_per_second": 1.985,
|
| 136 |
+
"step": 120
|
| 137 |
+
},
|
| 138 |
+
{
|
| 139 |
+
"entropy": 0.6709842771291733,
|
| 140 |
+
"epoch": 0.34869240348692404,
|
| 141 |
+
"grad_norm": 0.9135531187057495,
|
| 142 |
+
"learning_rate": 6.969125640924927e-05,
|
| 143 |
+
"loss": 0.5914147377014161,
|
| 144 |
+
"mean_token_accuracy": 0.8314545609056949,
|
| 145 |
+
"num_tokens": 327393.0,
|
| 146 |
+
"step": 140
|
| 147 |
+
},
|
| 148 |
+
{
|
| 149 |
+
"epoch": 0.34869240348692404,
|
| 150 |
+
"eval_entropy": 0.6584504666023476,
|
| 151 |
+
"eval_loss": 0.5849721431732178,
|
| 152 |
+
"eval_mean_token_accuracy": 0.8357757236375365,
|
| 153 |
+
"eval_num_tokens": 327393.0,
|
| 154 |
+
"eval_runtime": 86.3262,
|
| 155 |
+
"eval_samples_per_second": 15.94,
|
| 156 |
+
"eval_steps_per_second": 1.992,
|
| 157 |
+
"step": 140
|
| 158 |
+
},
|
| 159 |
+
{
|
| 160 |
+
"entropy": 0.6524647936224938,
|
| 161 |
+
"epoch": 0.398505603985056,
|
| 162 |
+
"grad_norm": 0.8651587963104248,
|
| 163 |
+
"learning_rate": 7.971877531705493e-05,
|
| 164 |
+
"loss": 0.5710843563079834,
|
| 165 |
+
"mean_token_accuracy": 0.8396127380430698,
|
| 166 |
+
"num_tokens": 373834.0,
|
| 167 |
+
"step": 160
|
| 168 |
+
},
|
| 169 |
+
{
|
| 170 |
+
"epoch": 0.398505603985056,
|
| 171 |
+
"eval_entropy": 0.6283470298661742,
|
| 172 |
+
"eval_loss": 0.5738973617553711,
|
| 173 |
+
"eval_mean_token_accuracy": 0.8379981181649274,
|
| 174 |
+
"eval_num_tokens": 373834.0,
|
| 175 |
+
"eval_runtime": 86.5619,
|
| 176 |
+
"eval_samples_per_second": 15.896,
|
| 177 |
+
"eval_steps_per_second": 1.987,
|
| 178 |
+
"step": 160
|
| 179 |
+
},
|
| 180 |
+
{
|
| 181 |
+
"entropy": 0.6450445972383022,
|
| 182 |
+
"epoch": 0.44831880448318806,
|
| 183 |
+
"grad_norm": 0.8661723732948303,
|
| 184 |
+
"learning_rate": 8.974629422486058e-05,
|
| 185 |
+
"loss": 0.5677794933319091,
|
| 186 |
+
"mean_token_accuracy": 0.8389350369572639,
|
| 187 |
+
"num_tokens": 422572.0,
|
| 188 |
+
"step": 180
|
| 189 |
+
},
|
| 190 |
+
{
|
| 191 |
+
"epoch": 0.44831880448318806,
|
| 192 |
+
"eval_entropy": 0.6142613257086554,
|
| 193 |
+
"eval_loss": 0.5698265433311462,
|
| 194 |
+
"eval_mean_token_accuracy": 0.8388577273418737,
|
| 195 |
+
"eval_num_tokens": 422572.0,
|
| 196 |
+
"eval_runtime": 86.4443,
|
| 197 |
+
"eval_samples_per_second": 15.918,
|
| 198 |
+
"eval_steps_per_second": 1.99,
|
| 199 |
+
"step": 180
|
| 200 |
+
},
|
| 201 |
+
{
|
| 202 |
+
"entropy": 0.6448334597051144,
|
| 203 |
+
"epoch": 0.49813200498132004,
|
| 204 |
+
"grad_norm": 0.9662242531776428,
|
| 205 |
+
"learning_rate": 9.977381313266624e-05,
|
| 206 |
+
"loss": 0.581433916091919,
|
| 207 |
+
"mean_token_accuracy": 0.8387043006718159,
|
| 208 |
+
"num_tokens": 471879.0,
|
| 209 |
+
"step": 200
|
| 210 |
+
},
|
| 211 |
+
{
|
| 212 |
+
"epoch": 0.49813200498132004,
|
| 213 |
+
"eval_entropy": 0.6154296522916749,
|
| 214 |
+
"eval_loss": 0.5660303831100464,
|
| 215 |
+
"eval_mean_token_accuracy": 0.8412494766850804,
|
| 216 |
+
"eval_num_tokens": 471879.0,
|
| 217 |
+
"eval_runtime": 86.3063,
|
| 218 |
+
"eval_samples_per_second": 15.943,
|
| 219 |
+
"eval_steps_per_second": 1.993,
|
| 220 |
+
"step": 200
|
| 221 |
+
},
|
| 222 |
+
{
|
| 223 |
+
"entropy": 0.6376728117465973,
|
| 224 |
+
"epoch": 0.547945205479452,
|
| 225 |
+
"grad_norm": 0.7618638873100281,
|
| 226 |
+
"learning_rate": 0.00010980133204047189,
|
| 227 |
+
"loss": 0.5678351402282715,
|
| 228 |
+
"mean_token_accuracy": 0.8404546812176704,
|
| 229 |
+
"num_tokens": 520984.0,
|
| 230 |
+
"step": 220
|
| 231 |
+
},
|
| 232 |
+
{
|
| 233 |
+
"epoch": 0.547945205479452,
|
| 234 |
+
"eval_entropy": 0.6181817033956217,
|
| 235 |
+
"eval_loss": 0.5663750171661377,
|
| 236 |
+
"eval_mean_token_accuracy": 0.8388350962899452,
|
| 237 |
+
"eval_num_tokens": 520984.0,
|
| 238 |
+
"eval_runtime": 86.5904,
|
| 239 |
+
"eval_samples_per_second": 15.891,
|
| 240 |
+
"eval_steps_per_second": 1.986,
|
| 241 |
+
"step": 220
|
| 242 |
+
},
|
| 243 |
+
{
|
| 244 |
+
"entropy": 0.6303176879882812,
|
| 245 |
+
"epoch": 0.597758405977584,
|
| 246 |
+
"grad_norm": 0.7571695446968079,
|
| 247 |
+
"learning_rate": 0.00011982885094827753,
|
| 248 |
+
"loss": 0.5502778053283691,
|
| 249 |
+
"mean_token_accuracy": 0.8429657347500324,
|
| 250 |
+
"num_tokens": 566596.0,
|
| 251 |
+
"step": 240
|
| 252 |
+
},
|
| 253 |
+
{
|
| 254 |
+
"epoch": 0.597758405977584,
|
| 255 |
+
"eval_entropy": 0.6252533817707107,
|
| 256 |
+
"eval_loss": 0.5570284128189087,
|
| 257 |
+
"eval_mean_token_accuracy": 0.8427327847064927,
|
| 258 |
+
"eval_num_tokens": 566596.0,
|
| 259 |
+
"eval_runtime": 86.4157,
|
| 260 |
+
"eval_samples_per_second": 15.923,
|
| 261 |
+
"eval_steps_per_second": 1.99,
|
| 262 |
+
"step": 240
|
| 263 |
+
},
|
| 264 |
+
{
|
| 265 |
+
"entropy": 0.6202544964849949,
|
| 266 |
+
"epoch": 0.6475716064757161,
|
| 267 |
+
"grad_norm": 0.6447190642356873,
|
| 268 |
+
"learning_rate": 0.00012985636985608318,
|
| 269 |
+
"loss": 0.5485352993011474,
|
| 270 |
+
"mean_token_accuracy": 0.844165726006031,
|
| 271 |
+
"num_tokens": 613603.0,
|
| 272 |
+
"step": 260
|
| 273 |
+
},
|
| 274 |
+
{
|
| 275 |
+
"epoch": 0.6475716064757161,
|
| 276 |
+
"eval_entropy": 0.6441633552312851,
|
| 277 |
+
"eval_loss": 0.5606644153594971,
|
| 278 |
+
"eval_mean_token_accuracy": 0.842403513054515,
|
| 279 |
+
"eval_num_tokens": 613603.0,
|
| 280 |
+
"eval_runtime": 86.6343,
|
| 281 |
+
"eval_samples_per_second": 15.883,
|
| 282 |
+
"eval_steps_per_second": 1.985,
|
| 283 |
+
"step": 260
|
| 284 |
+
},
|
| 285 |
+
{
|
| 286 |
+
"entropy": 0.6306711677461863,
|
| 287 |
+
"epoch": 0.6973848069738481,
|
| 288 |
+
"grad_norm": 0.7869907021522522,
|
| 289 |
+
"learning_rate": 0.00013988388876388883,
|
| 290 |
+
"loss": 0.5579307556152344,
|
| 291 |
+
"mean_token_accuracy": 0.841247134655714,
|
| 292 |
+
"num_tokens": 658565.0,
|
| 293 |
+
"step": 280
|
| 294 |
+
},
|
| 295 |
+
{
|
| 296 |
+
"epoch": 0.6973848069738481,
|
| 297 |
+
"eval_entropy": 0.6263934678809587,
|
| 298 |
+
"eval_loss": 0.5559113025665283,
|
| 299 |
+
"eval_mean_token_accuracy": 0.8427334743183713,
|
| 300 |
+
"eval_num_tokens": 658565.0,
|
| 301 |
+
"eval_runtime": 86.6403,
|
| 302 |
+
"eval_samples_per_second": 15.882,
|
| 303 |
+
"eval_steps_per_second": 1.985,
|
| 304 |
+
"step": 280
|
| 305 |
+
},
|
| 306 |
+
{
|
| 307 |
+
"entropy": 0.6385872110724449,
|
| 308 |
+
"epoch": 0.7471980074719801,
|
| 309 |
+
"grad_norm": 0.6679229736328125,
|
| 310 |
+
"learning_rate": 0.0001499114076716945,
|
| 311 |
+
"loss": 0.5667279720306396,
|
| 312 |
+
"mean_token_accuracy": 0.8389136254787445,
|
| 313 |
+
"num_tokens": 705680.0,
|
| 314 |
+
"step": 300
|
| 315 |
+
},
|
| 316 |
+
{
|
| 317 |
+
"epoch": 0.7471980074719801,
|
| 318 |
+
"eval_entropy": 0.6141417321077612,
|
| 319 |
+
"eval_loss": 0.5570600628852844,
|
| 320 |
+
"eval_mean_token_accuracy": 0.8437647996253745,
|
| 321 |
+
"eval_num_tokens": 705680.0,
|
| 322 |
+
"eval_runtime": 86.7588,
|
| 323 |
+
"eval_samples_per_second": 15.86,
|
| 324 |
+
"eval_steps_per_second": 1.983,
|
| 325 |
+
"step": 300
|
| 326 |
+
},
|
| 327 |
+
{
|
| 328 |
+
"entropy": 0.6199494235217571,
|
| 329 |
+
"epoch": 0.797011207970112,
|
| 330 |
+
"grad_norm": 0.7924400568008423,
|
| 331 |
+
"learning_rate": 0.00015993892657950015,
|
| 332 |
+
"loss": 0.5529299736022949,
|
| 333 |
+
"mean_token_accuracy": 0.8426973208785057,
|
| 334 |
+
"num_tokens": 752616.0,
|
| 335 |
+
"step": 320
|
| 336 |
+
},
|
| 337 |
+
{
|
| 338 |
+
"epoch": 0.797011207970112,
|
| 339 |
+
"eval_entropy": 0.6133768925833147,
|
| 340 |
+
"eval_loss": 0.556602418422699,
|
| 341 |
+
"eval_mean_token_accuracy": 0.8432947965555413,
|
| 342 |
+
"eval_num_tokens": 752616.0,
|
| 343 |
+
"eval_runtime": 86.492,
|
| 344 |
+
"eval_samples_per_second": 15.909,
|
| 345 |
+
"eval_steps_per_second": 1.989,
|
| 346 |
+
"step": 320
|
| 347 |
+
},
|
| 348 |
+
{
|
| 349 |
+
"entropy": 0.6203986253589392,
|
| 350 |
+
"epoch": 0.8468244084682441,
|
| 351 |
+
"grad_norm": 0.8364354372024536,
|
| 352 |
+
"learning_rate": 0.00016996644548730578,
|
| 353 |
+
"loss": 0.5551144123077393,
|
| 354 |
+
"mean_token_accuracy": 0.8432973213493824,
|
| 355 |
+
"num_tokens": 797151.0,
|
| 356 |
+
"step": 340
|
| 357 |
+
},
|
| 358 |
+
{
|
| 359 |
+
"epoch": 0.8468244084682441,
|
| 360 |
+
"eval_entropy": 0.6017442844634833,
|
| 361 |
+
"eval_loss": 0.5566568374633789,
|
| 362 |
+
"eval_mean_token_accuracy": 0.8437666123689607,
|
| 363 |
+
"eval_num_tokens": 797151.0,
|
| 364 |
+
"eval_runtime": 86.5552,
|
| 365 |
+
"eval_samples_per_second": 15.897,
|
| 366 |
+
"eval_steps_per_second": 1.987,
|
| 367 |
+
"step": 340
|
| 368 |
+
},
|
| 369 |
+
{
|
| 370 |
+
"entropy": 0.6341533534228802,
|
| 371 |
+
"epoch": 0.8966376089663761,
|
| 372 |
+
"grad_norm": 0.7783445715904236,
|
| 373 |
+
"learning_rate": 0.00017999396439511144,
|
| 374 |
+
"loss": 0.5669133186340332,
|
| 375 |
+
"mean_token_accuracy": 0.8379446342587471,
|
| 376 |
+
"num_tokens": 843585.0,
|
| 377 |
+
"step": 360
|
| 378 |
+
},
|
| 379 |
+
{
|
| 380 |
+
"epoch": 0.8966376089663761,
|
| 381 |
+
"eval_entropy": 0.6055107958788095,
|
| 382 |
+
"eval_loss": 0.5599350333213806,
|
| 383 |
+
"eval_mean_token_accuracy": 0.8435030894917112,
|
| 384 |
+
"eval_num_tokens": 843585.0,
|
| 385 |
+
"eval_runtime": 86.4814,
|
| 386 |
+
"eval_samples_per_second": 15.911,
|
| 387 |
+
"eval_steps_per_second": 1.989,
|
| 388 |
+
"step": 360
|
| 389 |
+
},
|
| 390 |
+
{
|
| 391 |
+
"entropy": 0.6306198488920927,
|
| 392 |
+
"epoch": 0.9464508094645081,
|
| 393 |
+
"grad_norm": 0.8449786901473999,
|
| 394 |
+
"learning_rate": 0.0001900214833029171,
|
| 395 |
+
"loss": 0.5739435195922852,
|
| 396 |
+
"mean_token_accuracy": 0.8393832489848136,
|
| 397 |
+
"num_tokens": 889842.0,
|
| 398 |
+
"step": 380
|
| 399 |
+
},
|
| 400 |
+
{
|
| 401 |
+
"epoch": 0.9464508094645081,
|
| 402 |
+
"eval_entropy": 0.6129532439071078,
|
| 403 |
+
"eval_loss": 0.5566295981407166,
|
| 404 |
+
"eval_mean_token_accuracy": 0.8430350880290187,
|
| 405 |
+
"eval_num_tokens": 889842.0,
|
| 406 |
+
"eval_runtime": 86.4643,
|
| 407 |
+
"eval_samples_per_second": 15.914,
|
| 408 |
+
"eval_steps_per_second": 1.989,
|
| 409 |
+
"step": 380
|
| 410 |
+
},
|
| 411 |
+
{
|
| 412 |
+
"entropy": 0.6203123550862074,
|
| 413 |
+
"epoch": 0.9962640099626401,
|
| 414 |
+
"grad_norm": 0.7334314584732056,
|
| 415 |
+
"learning_rate": 0.00020004900221072276,
|
| 416 |
+
"loss": 0.5547565937042236,
|
| 417 |
+
"mean_token_accuracy": 0.8403573960065842,
|
| 418 |
+
"num_tokens": 935589.0,
|
| 419 |
+
"step": 400
|
| 420 |
+
},
|
| 421 |
+
{
|
| 422 |
+
"epoch": 0.9962640099626401,
|
| 423 |
+
"eval_entropy": 0.6275761647279873,
|
| 424 |
+
"eval_loss": 0.5621116757392883,
|
| 425 |
+
"eval_mean_token_accuracy": 0.841587379228237,
|
| 426 |
+
"eval_num_tokens": 935589.0,
|
| 427 |
+
"eval_runtime": 86.4748,
|
| 428 |
+
"eval_samples_per_second": 15.912,
|
| 429 |
+
"eval_steps_per_second": 1.989,
|
| 430 |
+
"step": 400
|
| 431 |
+
},
|
| 432 |
+
{
|
| 433 |
+
"entropy": 0.5795013002860241,
|
| 434 |
+
"epoch": 1.0448318804483188,
|
| 435 |
+
"grad_norm": 0.8858296871185303,
|
| 436 |
+
"learning_rate": 0.0002015421505577756,
|
| 437 |
+
"loss": 0.5183939933776855,
|
| 438 |
+
"mean_token_accuracy": 0.850081592034071,
|
| 439 |
+
"num_tokens": 980589.0,
|
| 440 |
+
"step": 420
|
| 441 |
+
},
|
| 442 |
+
{
|
| 443 |
+
"epoch": 1.0448318804483188,
|
| 444 |
+
"eval_entropy": 0.5583065545489622,
|
| 445 |
+
"eval_loss": 0.5605642199516296,
|
| 446 |
+
"eval_mean_token_accuracy": 0.8439708411000496,
|
| 447 |
+
"eval_num_tokens": 980589.0,
|
| 448 |
+
"eval_runtime": 86.5422,
|
| 449 |
+
"eval_samples_per_second": 15.9,
|
| 450 |
+
"eval_steps_per_second": 1.987,
|
| 451 |
+
"step": 420
|
| 452 |
+
},
|
| 453 |
+
{
|
| 454 |
+
"entropy": 0.5671238023787737,
|
| 455 |
+
"epoch": 1.0946450809464507,
|
| 456 |
+
"grad_norm": 0.6882498264312744,
|
| 457 |
+
"learning_rate": 0.00020150112347025443,
|
| 458 |
+
"loss": 0.5077326774597168,
|
| 459 |
+
"mean_token_accuracy": 0.8489868573844432,
|
| 460 |
+
"num_tokens": 1027852.0,
|
| 461 |
+
"step": 440
|
| 462 |
+
},
|
| 463 |
+
{
|
| 464 |
+
"epoch": 1.0946450809464507,
|
| 465 |
+
"eval_entropy": 0.5868900277933409,
|
| 466 |
+
"eval_loss": 0.5602695345878601,
|
| 467 |
+
"eval_mean_token_accuracy": 0.8428842161977014,
|
| 468 |
+
"eval_num_tokens": 1027852.0,
|
| 469 |
+
"eval_runtime": 86.623,
|
| 470 |
+
"eval_samples_per_second": 15.885,
|
| 471 |
+
"eval_steps_per_second": 1.986,
|
| 472 |
+
"step": 440
|
| 473 |
+
},
|
| 474 |
+
{
|
| 475 |
+
"entropy": 0.5533561781048775,
|
| 476 |
+
"epoch": 1.1444582814445827,
|
| 477 |
+
"grad_norm": 0.7717723250389099,
|
| 478 |
+
"learning_rate": 0.0002014297192297181,
|
| 479 |
+
"loss": 0.4954517364501953,
|
| 480 |
+
"mean_token_accuracy": 0.8529035650193691,
|
| 481 |
+
"num_tokens": 1077649.0,
|
| 482 |
+
"step": 460
|
| 483 |
+
},
|
| 484 |
+
{
|
| 485 |
+
"epoch": 1.1444582814445827,
|
| 486 |
+
"eval_entropy": 0.5600803743961246,
|
| 487 |
+
"eval_loss": 0.5608077645301819,
|
| 488 |
+
"eval_mean_token_accuracy": 0.8445036771685578,
|
| 489 |
+
"eval_num_tokens": 1077649.0,
|
| 490 |
+
"eval_runtime": 86.1316,
|
| 491 |
+
"eval_samples_per_second": 15.976,
|
| 492 |
+
"eval_steps_per_second": 1.997,
|
| 493 |
+
"step": 460
|
| 494 |
+
},
|
| 495 |
+
{
|
| 496 |
+
"entropy": 0.5692154694348573,
|
| 497 |
+
"epoch": 1.1942714819427147,
|
| 498 |
+
"grad_norm": 0.7322827577590942,
|
| 499 |
+
"learning_rate": 0.0002013279593707117,
|
| 500 |
+
"loss": 0.505049467086792,
|
| 501 |
+
"mean_token_accuracy": 0.8551576808094978,
|
| 502 |
+
"num_tokens": 1124872.0,
|
| 503 |
+
"step": 480
|
| 504 |
+
},
|
| 505 |
+
{
|
| 506 |
+
"epoch": 1.1942714819427147,
|
| 507 |
+
"eval_entropy": 0.5732695829383162,
|
| 508 |
+
"eval_loss": 0.5594323873519897,
|
| 509 |
+
"eval_mean_token_accuracy": 0.8449713407560836,
|
| 510 |
+
"eval_num_tokens": 1124872.0,
|
| 511 |
+
"eval_runtime": 86.2726,
|
| 512 |
+
"eval_samples_per_second": 15.949,
|
| 513 |
+
"eval_steps_per_second": 1.994,
|
| 514 |
+
"step": 480
|
| 515 |
+
},
|
| 516 |
+
{
|
| 517 |
+
"entropy": 0.5817618492990733,
|
| 518 |
+
"epoch": 1.244084682440847,
|
| 519 |
+
"grad_norm": 1.1776764392852783,
|
| 520 |
+
"learning_rate": 0.0002011958745826208,
|
| 521 |
+
"loss": 0.5137609958648681,
|
| 522 |
+
"mean_token_accuracy": 0.8521522544324398,
|
| 523 |
+
"num_tokens": 1168698.0,
|
| 524 |
+
"step": 500
|
| 525 |
+
},
|
| 526 |
+
{
|
| 527 |
+
"epoch": 1.244084682440847,
|
| 528 |
+
"eval_entropy": 0.5662581343636957,
|
| 529 |
+
"eval_loss": 0.5595026016235352,
|
| 530 |
+
"eval_mean_token_accuracy": 0.8441977164773053,
|
| 531 |
+
"eval_num_tokens": 1168698.0,
|
| 532 |
+
"eval_runtime": 86.7261,
|
| 533 |
+
"eval_samples_per_second": 15.866,
|
| 534 |
+
"eval_steps_per_second": 1.983,
|
| 535 |
+
"step": 500
|
| 536 |
+
},
|
| 537 |
+
{
|
| 538 |
+
"entropy": 0.5712925456464291,
|
| 539 |
+
"epoch": 1.293897882938979,
|
| 540 |
+
"grad_norm": 0.7960361838340759,
|
| 541 |
+
"learning_rate": 0.0002010335047004159,
|
| 542 |
+
"loss": 0.5134767532348633,
|
| 543 |
+
"mean_token_accuracy": 0.8513577707111836,
|
| 544 |
+
"num_tokens": 1216679.0,
|
| 545 |
+
"step": 520
|
| 546 |
+
},
|
| 547 |
+
{
|
| 548 |
+
"epoch": 1.293897882938979,
|
| 549 |
+
"eval_entropy": 0.5441222797299541,
|
| 550 |
+
"eval_loss": 0.5535460114479065,
|
| 551 |
+
"eval_mean_token_accuracy": 0.8450886118550633,
|
| 552 |
+
"eval_num_tokens": 1216679.0,
|
| 553 |
+
"eval_runtime": 86.2675,
|
| 554 |
+
"eval_samples_per_second": 15.95,
|
| 555 |
+
"eval_steps_per_second": 1.994,
|
| 556 |
+
"step": 520
|
| 557 |
+
},
|
| 558 |
+
{
|
| 559 |
+
"entropy": 0.5787045754492283,
|
| 560 |
+
"epoch": 1.3437110834371109,
|
| 561 |
+
"grad_norm": 0.9205410480499268,
|
| 562 |
+
"learning_rate": 0.00020084089869263887,
|
| 563 |
+
"loss": 0.5119701862335205,
|
| 564 |
+
"mean_token_accuracy": 0.8503516331315041,
|
| 565 |
+
"num_tokens": 1261365.0,
|
| 566 |
+
"step": 540
|
| 567 |
+
},
|
| 568 |
+
{
|
| 569 |
+
"epoch": 1.3437110834371109,
|
| 570 |
+
"eval_entropy": 0.5744457827057949,
|
| 571 |
+
"eval_loss": 0.5514978766441345,
|
| 572 |
+
"eval_mean_token_accuracy": 0.845929987901865,
|
| 573 |
+
"eval_num_tokens": 1261365.0,
|
| 574 |
+
"eval_runtime": 86.2299,
|
| 575 |
+
"eval_samples_per_second": 15.957,
|
| 576 |
+
"eval_steps_per_second": 1.995,
|
| 577 |
+
"step": 540
|
| 578 |
+
},
|
| 579 |
+
{
|
| 580 |
+
"entropy": 0.5739392962306737,
|
| 581 |
+
"epoch": 1.3935242839352429,
|
| 582 |
+
"grad_norm": 0.7475653886795044,
|
| 583 |
+
"learning_rate": 0.00020061811464663464,
|
| 584 |
+
"loss": 0.5189042091369629,
|
| 585 |
+
"mean_token_accuracy": 0.8492388024926185,
|
| 586 |
+
"num_tokens": 1306879.0,
|
| 587 |
+
"step": 560
|
| 588 |
+
},
|
| 589 |
+
{
|
| 590 |
+
"epoch": 1.3935242839352429,
|
| 591 |
+
"eval_entropy": 0.6116398271433142,
|
| 592 |
+
"eval_loss": 0.551732063293457,
|
| 593 |
+
"eval_mean_token_accuracy": 0.8450756967067719,
|
| 594 |
+
"eval_num_tokens": 1306879.0,
|
| 595 |
+
"eval_runtime": 86.6081,
|
| 596 |
+
"eval_samples_per_second": 15.888,
|
| 597 |
+
"eval_steps_per_second": 1.986,
|
| 598 |
+
"step": 560
|
| 599 |
+
},
|
| 600 |
+
{
|
| 601 |
+
"entropy": 0.5755622573196888,
|
| 602 |
+
"epoch": 1.4433374844333748,
|
| 603 |
+
"grad_norm": 0.8218411803245544,
|
| 604 |
+
"learning_rate": 0.00020036521975103286,
|
| 605 |
+
"loss": 0.5106248378753662,
|
| 606 |
+
"mean_token_accuracy": 0.8506785586476326,
|
| 607 |
+
"num_tokens": 1353534.0,
|
| 608 |
+
"step": 580
|
| 609 |
+
},
|
| 610 |
+
{
|
| 611 |
+
"epoch": 1.4433374844333748,
|
| 612 |
+
"eval_entropy": 0.5906928708386976,
|
| 613 |
+
"eval_loss": 0.551278829574585,
|
| 614 |
+
"eval_mean_token_accuracy": 0.8462819308042526,
|
| 615 |
+
"eval_num_tokens": 1353534.0,
|
| 616 |
+
"eval_runtime": 86.5438,
|
| 617 |
+
"eval_samples_per_second": 15.899,
|
| 618 |
+
"eval_steps_per_second": 1.987,
|
| 619 |
+
"step": 580
|
| 620 |
+
},
|
| 621 |
+
{
|
| 622 |
+
"entropy": 0.5694822132587433,
|
| 623 |
+
"epoch": 1.4931506849315068,
|
| 624 |
+
"grad_norm": 0.8880652189254761,
|
| 625 |
+
"learning_rate": 0.00020008229027548475,
|
| 626 |
+
"loss": 0.5140334606170655,
|
| 627 |
+
"mean_token_accuracy": 0.8521522797644139,
|
| 628 |
+
"num_tokens": 1399537.0,
|
| 629 |
+
"step": 600
|
| 630 |
+
},
|
| 631 |
+
{
|
| 632 |
+
"epoch": 1.4931506849315068,
|
| 633 |
+
"eval_entropy": 0.5599641964532608,
|
| 634 |
+
"eval_loss": 0.5501875877380371,
|
| 635 |
+
"eval_mean_token_accuracy": 0.8467660788879838,
|
| 636 |
+
"eval_num_tokens": 1399537.0,
|
| 637 |
+
"eval_runtime": 86.6458,
|
| 638 |
+
"eval_samples_per_second": 15.881,
|
| 639 |
+
"eval_steps_per_second": 1.985,
|
| 640 |
+
"step": 600
|
| 641 |
+
},
|
| 642 |
+
{
|
| 643 |
+
"entropy": 0.5675108034163714,
|
| 644 |
+
"epoch": 1.5429638854296388,
|
| 645 |
+
"grad_norm": 0.837087094783783,
|
| 646 |
+
"learning_rate": 0.0001997694115476612,
|
| 647 |
+
"loss": 0.5099846363067627,
|
| 648 |
+
"mean_token_accuracy": 0.8543680295348167,
|
| 649 |
+
"num_tokens": 1448422.0,
|
| 650 |
+
"step": 620
|
| 651 |
+
},
|
| 652 |
+
{
|
| 653 |
+
"epoch": 1.5429638854296388,
|
| 654 |
+
"eval_entropy": 0.5728072581249614,
|
| 655 |
+
"eval_loss": 0.5445425510406494,
|
| 656 |
+
"eval_mean_token_accuracy": 0.8474342175001321,
|
| 657 |
+
"eval_num_tokens": 1448422.0,
|
| 658 |
+
"eval_runtime": 86.4859,
|
| 659 |
+
"eval_samples_per_second": 15.91,
|
| 660 |
+
"eval_steps_per_second": 1.989,
|
| 661 |
+
"step": 620
|
| 662 |
+
},
|
| 663 |
+
{
|
| 664 |
+
"entropy": 0.5700885068625212,
|
| 665 |
+
"epoch": 1.592777085927771,
|
| 666 |
+
"grad_norm": 0.6598765850067139,
|
| 667 |
+
"learning_rate": 0.000199426677927519,
|
| 668 |
+
"loss": 0.5122694969177246,
|
| 669 |
+
"mean_token_accuracy": 0.8519927568733692,
|
| 670 |
+
"num_tokens": 1495009.0,
|
| 671 |
+
"step": 640
|
| 672 |
+
},
|
| 673 |
+
{
|
| 674 |
+
"epoch": 1.592777085927771,
|
| 675 |
+
"eval_entropy": 0.5476993622128353,
|
| 676 |
+
"eval_loss": 0.5427973866462708,
|
| 677 |
+
"eval_mean_token_accuracy": 0.8478512147138285,
|
| 678 |
+
"eval_num_tokens": 1495009.0,
|
| 679 |
+
"eval_runtime": 86.4172,
|
| 680 |
+
"eval_samples_per_second": 15.923,
|
| 681 |
+
"eval_steps_per_second": 1.99,
|
| 682 |
+
"step": 640
|
| 683 |
+
},
|
| 684 |
+
{
|
| 685 |
+
"entropy": 0.5829229176044464,
|
| 686 |
+
"epoch": 1.6425902864259028,
|
| 687 |
+
"grad_norm": 0.6965194940567017,
|
| 688 |
+
"learning_rate": 0.00019905419277884342,
|
| 689 |
+
"loss": 0.5253659725189209,
|
| 690 |
+
"mean_token_accuracy": 0.8493309423327446,
|
| 691 |
+
"num_tokens": 1536932.0,
|
| 692 |
+
"step": 660
|
| 693 |
+
},
|
| 694 |
+
{
|
| 695 |
+
"epoch": 1.6425902864259028,
|
| 696 |
+
"eval_entropy": 0.5666290084983028,
|
| 697 |
+
"eval_loss": 0.5467478036880493,
|
| 698 |
+
"eval_mean_token_accuracy": 0.8479407703460649,
|
| 699 |
+
"eval_num_tokens": 1536932.0,
|
| 700 |
+
"eval_runtime": 86.4414,
|
| 701 |
+
"eval_samples_per_second": 15.918,
|
| 702 |
+
"eval_steps_per_second": 1.99,
|
| 703 |
+
"step": 660
|
| 704 |
+
},
|
| 705 |
+
{
|
| 706 |
+
"entropy": 0.5498311135917902,
|
| 707 |
+
"epoch": 1.692403486924035,
|
| 708 |
+
"grad_norm": 0.636583685874939,
|
| 709 |
+
"learning_rate": 0.00019865206843807482,
|
| 710 |
+
"loss": 0.49981012344360354,
|
| 711 |
+
"mean_token_accuracy": 0.8560848504304885,
|
| 712 |
+
"num_tokens": 1585718.0,
|
| 713 |
+
"step": 680
|
| 714 |
+
},
|
| 715 |
+
{
|
| 716 |
+
"epoch": 1.692403486924035,
|
| 717 |
+
"eval_entropy": 0.539117265406043,
|
| 718 |
+
"eval_loss": 0.53994220495224,
|
| 719 |
+
"eval_mean_token_accuracy": 0.8488582601380903,
|
| 720 |
+
"eval_num_tokens": 1585718.0,
|
| 721 |
+
"eval_runtime": 86.5296,
|
| 722 |
+
"eval_samples_per_second": 15.902,
|
| 723 |
+
"eval_steps_per_second": 1.988,
|
| 724 |
+
"step": 680
|
| 725 |
+
},
|
| 726 |
+
{
|
| 727 |
+
"entropy": 0.5543891470879316,
|
| 728 |
+
"epoch": 1.7422166874221667,
|
| 729 |
+
"grad_norm": 0.6068442463874817,
|
| 730 |
+
"learning_rate": 0.0001982204261804297,
|
| 731 |
+
"loss": 0.498047399520874,
|
| 732 |
+
"mean_token_accuracy": 0.8554679051041603,
|
| 733 |
+
"num_tokens": 1635718.0,
|
| 734 |
+
"step": 700
|
| 735 |
+
},
|
| 736 |
+
{
|
| 737 |
+
"epoch": 1.7422166874221667,
|
| 738 |
+
"eval_entropy": 0.5703774151760478,
|
| 739 |
+
"eval_loss": 0.5300245881080627,
|
| 740 |
+
"eval_mean_token_accuracy": 0.850798153946566,
|
| 741 |
+
"eval_num_tokens": 1635718.0,
|
| 742 |
+
"eval_runtime": 86.6456,
|
| 743 |
+
"eval_samples_per_second": 15.881,
|
| 744 |
+
"eval_steps_per_second": 1.985,
|
| 745 |
+
"step": 700
|
| 746 |
+
},
|
| 747 |
+
{
|
| 748 |
+
"entropy": 0.546524541825056,
|
| 749 |
+
"epoch": 1.792029887920299,
|
| 750 |
+
"grad_norm": 0.7274155020713806,
|
| 751 |
+
"learning_rate": 0.00019775939618332566,
|
| 752 |
+
"loss": 0.4988589286804199,
|
| 753 |
+
"mean_token_accuracy": 0.853422473371029,
|
| 754 |
+
"num_tokens": 1681291.0,
|
| 755 |
+
"step": 720
|
| 756 |
+
},
|
| 757 |
+
{
|
| 758 |
+
"epoch": 1.792029887920299,
|
| 759 |
+
"eval_entropy": 0.5614905688305234,
|
| 760 |
+
"eval_loss": 0.5350332260131836,
|
| 761 |
+
"eval_mean_token_accuracy": 0.8492204359797544,
|
| 762 |
+
"eval_num_tokens": 1681291.0,
|
| 763 |
+
"eval_runtime": 86.7581,
|
| 764 |
+
"eval_samples_per_second": 15.86,
|
| 765 |
+
"eval_steps_per_second": 1.983,
|
| 766 |
+
"step": 720
|
| 767 |
+
},
|
| 768 |
+
{
|
| 769 |
+
"entropy": 0.5519792139530182,
|
| 770 |
+
"epoch": 1.841843088418431,
|
| 771 |
+
"grad_norm": 0.663466215133667,
|
| 772 |
+
"learning_rate": 0.00019726911748712167,
|
| 773 |
+
"loss": 0.5099314212799072,
|
| 774 |
+
"mean_token_accuracy": 0.848412600159645,
|
| 775 |
+
"num_tokens": 1729102.0,
|
| 776 |
+
"step": 740
|
| 777 |
+
},
|
| 778 |
+
{
|
| 779 |
+
"epoch": 1.841843088418431,
|
| 780 |
+
"eval_entropy": 0.5583519090053647,
|
| 781 |
+
"eval_loss": 0.530483603477478,
|
| 782 |
+
"eval_mean_token_accuracy": 0.8500003374593202,
|
| 783 |
+
"eval_num_tokens": 1729102.0,
|
| 784 |
+
"eval_runtime": 86.3961,
|
| 785 |
+
"eval_samples_per_second": 15.927,
|
| 786 |
+
"eval_steps_per_second": 1.991,
|
| 787 |
+
"step": 740
|
| 788 |
+
},
|
| 789 |
+
{
|
| 790 |
+
"entropy": 0.5454779766499996,
|
| 791 |
+
"epoch": 1.891656288916563,
|
| 792 |
+
"grad_norm": 0.890394926071167,
|
| 793 |
+
"learning_rate": 0.00019674973795318548,
|
| 794 |
+
"loss": 0.4931994915008545,
|
| 795 |
+
"mean_token_accuracy": 0.8540832489728928,
|
| 796 |
+
"num_tokens": 1773578.0,
|
| 797 |
+
"step": 760
|
| 798 |
+
},
|
| 799 |
+
{
|
| 800 |
+
"epoch": 1.891656288916563,
|
| 801 |
+
"eval_entropy": 0.572755502406941,
|
| 802 |
+
"eval_loss": 0.5415747761726379,
|
| 803 |
+
"eval_mean_token_accuracy": 0.8444425803284312,
|
| 804 |
+
"eval_num_tokens": 1773578.0,
|
| 805 |
+
"eval_runtime": 86.4323,
|
| 806 |
+
"eval_samples_per_second": 15.92,
|
| 807 |
+
"eval_steps_per_second": 1.99,
|
| 808 |
+
"step": 760
|
| 809 |
+
},
|
| 810 |
+
{
|
| 811 |
+
"entropy": 0.5392089951783419,
|
| 812 |
+
"epoch": 1.9414694894146949,
|
| 813 |
+
"grad_norm": 0.632411777973175,
|
| 814 |
+
"learning_rate": 0.00019620141421930058,
|
| 815 |
+
"loss": 0.4957888603210449,
|
| 816 |
+
"mean_token_accuracy": 0.8549866065382957,
|
| 817 |
+
"num_tokens": 1821725.0,
|
| 818 |
+
"step": 780
|
| 819 |
+
},
|
| 820 |
+
{
|
| 821 |
+
"epoch": 1.9414694894146949,
|
| 822 |
+
"eval_entropy": 0.540764772961306,
|
| 823 |
+
"eval_loss": 0.5327216386795044,
|
| 824 |
+
"eval_mean_token_accuracy": 0.850631088364956,
|
| 825 |
+
"eval_num_tokens": 1821725.0,
|
| 826 |
+
"eval_runtime": 86.8097,
|
| 827 |
+
"eval_samples_per_second": 15.851,
|
| 828 |
+
"eval_steps_per_second": 1.981,
|
| 829 |
+
"step": 780
|
| 830 |
+
},
|
| 831 |
+
{
|
| 832 |
+
"entropy": 0.5674678739160299,
|
| 833 |
+
"epoch": 1.9912826899128269,
|
| 834 |
+
"grad_norm": 0.6958843469619751,
|
| 835 |
+
"learning_rate": 0.0001956243116524263,
|
| 836 |
+
"loss": 0.504389762878418,
|
| 837 |
+
"mean_token_accuracy": 0.8527948908507824,
|
| 838 |
+
"num_tokens": 1868431.0,
|
| 839 |
+
"step": 800
|
| 840 |
+
},
|
| 841 |
+
{
|
| 842 |
+
"epoch": 1.9912826899128269,
|
| 843 |
+
"eval_entropy": 0.530262403190136,
|
| 844 |
+
"eval_loss": 0.5308871865272522,
|
| 845 |
+
"eval_mean_token_accuracy": 0.8522498046242913,
|
| 846 |
+
"eval_num_tokens": 1868431.0,
|
| 847 |
+
"eval_runtime": 86.7942,
|
| 848 |
+
"eval_samples_per_second": 15.854,
|
| 849 |
+
"eval_steps_per_second": 1.982,
|
| 850 |
+
"step": 800
|
| 851 |
+
},
|
| 852 |
+
{
|
| 853 |
+
"entropy": 0.4742849511213792,
|
| 854 |
+
"epoch": 2.0398505603985058,
|
| 855 |
+
"grad_norm": 0.6941492557525635,
|
| 856 |
+
"learning_rate": 0.00019501860429882556,
|
| 857 |
+
"loss": 0.418599271774292,
|
| 858 |
+
"mean_token_accuracy": 0.8748210859604371,
|
| 859 |
+
"num_tokens": 1915280.0,
|
| 860 |
+
"step": 820
|
| 861 |
+
},
|
| 862 |
+
{
|
| 863 |
+
"epoch": 2.0398505603985058,
|
| 864 |
+
"eval_entropy": 0.504602165069691,
|
| 865 |
+
"eval_loss": 0.542878270149231,
|
| 866 |
+
"eval_mean_token_accuracy": 0.8507604484641275,
|
| 867 |
+
"eval_num_tokens": 1915280.0,
|
| 868 |
+
"eval_runtime": 86.7841,
|
| 869 |
+
"eval_samples_per_second": 15.855,
|
| 870 |
+
"eval_steps_per_second": 1.982,
|
| 871 |
+
"step": 820
|
| 872 |
+
},
|
| 873 |
+
{
|
| 874 |
+
"entropy": 0.45857742577791216,
|
| 875 |
+
"epoch": 2.0896637608966375,
|
| 876 |
+
"grad_norm": 0.5791997909545898,
|
| 877 |
+
"learning_rate": 0.00019438447483157478,
|
| 878 |
+
"loss": 0.399777889251709,
|
| 879 |
+
"mean_token_accuracy": 0.8754058346152306,
|
| 880 |
+
"num_tokens": 1965306.0,
|
| 881 |
+
"step": 840
|
| 882 |
+
},
|
| 883 |
+
{
|
| 884 |
+
"epoch": 2.0896637608966375,
|
| 885 |
+
"eval_entropy": 0.5028848362176918,
|
| 886 |
+
"eval_loss": 0.5356478095054626,
|
| 887 |
+
"eval_mean_token_accuracy": 0.8525635412959165,
|
| 888 |
+
"eval_num_tokens": 1965306.0,
|
| 889 |
+
"eval_runtime": 86.6707,
|
| 890 |
+
"eval_samples_per_second": 15.876,
|
| 891 |
+
"eval_steps_per_second": 1.985,
|
| 892 |
+
"step": 840
|
| 893 |
+
},
|
| 894 |
+
{
|
| 895 |
+
"entropy": 0.4869446292519569,
|
| 896 |
+
"epoch": 2.1394769613947697,
|
| 897 |
+
"grad_norm": 0.6483516693115234,
|
| 898 |
+
"learning_rate": 0.00019372211449547223,
|
| 899 |
+
"loss": 0.40715818405151366,
|
| 900 |
+
"mean_token_accuracy": 0.875113020837307,
|
| 901 |
+
"num_tokens": 2008562.0,
|
| 902 |
+
"step": 860
|
| 903 |
+
},
|
| 904 |
+
{
|
| 905 |
+
"epoch": 2.1394769613947697,
|
| 906 |
+
"eval_entropy": 0.4928991326759028,
|
| 907 |
+
"eval_loss": 0.5419561862945557,
|
| 908 |
+
"eval_mean_token_accuracy": 0.8516040146350861,
|
| 909 |
+
"eval_num_tokens": 2008562.0,
|
| 910 |
+
"eval_runtime": 87.0686,
|
| 911 |
+
"eval_samples_per_second": 15.804,
|
| 912 |
+
"eval_steps_per_second": 1.975,
|
| 913 |
+
"step": 860
|
| 914 |
+
},
|
| 915 |
+
{
|
| 916 |
+
"entropy": 0.45819590501487256,
|
| 917 |
+
"epoch": 2.1892901618929015,
|
| 918 |
+
"grad_norm": 0.6661920547485352,
|
| 919 |
+
"learning_rate": 0.00019303172304936108,
|
| 920 |
+
"loss": 0.39511430263519287,
|
| 921 |
+
"mean_token_accuracy": 0.8780680045485496,
|
| 922 |
+
"num_tokens": 2056474.0,
|
| 923 |
+
"step": 880
|
| 924 |
+
},
|
| 925 |
+
{
|
| 926 |
+
"epoch": 2.1892901618929015,
|
| 927 |
+
"eval_entropy": 0.48602560647698334,
|
| 928 |
+
"eval_loss": 0.5436084866523743,
|
| 929 |
+
"eval_mean_token_accuracy": 0.8500938470973525,
|
| 930 |
+
"eval_num_tokens": 2056474.0,
|
| 931 |
+
"eval_runtime": 86.6809,
|
| 932 |
+
"eval_samples_per_second": 15.874,
|
| 933 |
+
"eval_steps_per_second": 1.984,
|
| 934 |
+
"step": 880
|
| 935 |
+
},
|
| 936 |
+
{
|
| 937 |
+
"entropy": 0.4780638810247183,
|
| 938 |
+
"epoch": 2.2391033623910337,
|
| 939 |
+
"grad_norm": 0.6870484352111816,
|
| 940 |
+
"learning_rate": 0.0001923135087058851,
|
| 941 |
+
"loss": 0.4061615467071533,
|
| 942 |
+
"mean_token_accuracy": 0.8766494184732437,
|
| 943 |
+
"num_tokens": 2103543.0,
|
| 944 |
+
"step": 900
|
| 945 |
+
},
|
| 946 |
+
{
|
| 947 |
+
"epoch": 2.2391033623910337,
|
| 948 |
+
"eval_entropy": 0.48236206035281337,
|
| 949 |
+
"eval_loss": 0.5446090698242188,
|
| 950 |
+
"eval_mean_token_accuracy": 0.8507725513258646,
|
| 951 |
+
"eval_num_tokens": 2103543.0,
|
| 952 |
+
"eval_runtime": 86.7398,
|
| 953 |
+
"eval_samples_per_second": 15.864,
|
| 954 |
+
"eval_steps_per_second": 1.983,
|
| 955 |
+
"step": 900
|
| 956 |
+
},
|
| 957 |
+
{
|
| 958 |
+
"entropy": 0.463029869645834,
|
| 959 |
+
"epoch": 2.2889165628891655,
|
| 960 |
+
"grad_norm": 0.6894590854644775,
|
| 961 |
+
"learning_rate": 0.00019156768806869427,
|
| 962 |
+
"loss": 0.39602413177490237,
|
| 963 |
+
"mean_token_accuracy": 0.876420046389103,
|
| 964 |
+
"num_tokens": 2147861.0,
|
| 965 |
+
"step": 920
|
| 966 |
+
},
|
| 967 |
+
{
|
| 968 |
+
"epoch": 2.2889165628891655,
|
| 969 |
+
"eval_entropy": 0.4904779093556626,
|
| 970 |
+
"eval_loss": 0.5404934287071228,
|
| 971 |
+
"eval_mean_token_accuracy": 0.852238280828609,
|
| 972 |
+
"eval_num_tokens": 2147861.0,
|
| 973 |
+
"eval_runtime": 86.5348,
|
| 974 |
+
"eval_samples_per_second": 15.901,
|
| 975 |
+
"eval_steps_per_second": 1.988,
|
| 976 |
+
"step": 920
|
| 977 |
+
},
|
| 978 |
+
{
|
| 979 |
+
"entropy": 0.4817025110125542,
|
| 980 |
+
"epoch": 2.3387297633872977,
|
| 981 |
+
"grad_norm": 0.7756227254867554,
|
| 982 |
+
"learning_rate": 0.00019079448606712033,
|
| 983 |
+
"loss": 0.4177968502044678,
|
| 984 |
+
"mean_token_accuracy": 0.8712256088852882,
|
| 985 |
+
"num_tokens": 2190561.0,
|
| 986 |
+
"step": 940
|
| 987 |
+
},
|
| 988 |
+
{
|
| 989 |
+
"epoch": 2.3387297633872977,
|
| 990 |
+
"eval_entropy": 0.5153802815218305,
|
| 991 |
+
"eval_loss": 0.5424937605857849,
|
| 992 |
+
"eval_mean_token_accuracy": 0.8506565759348315,
|
| 993 |
+
"eval_num_tokens": 2190561.0,
|
| 994 |
+
"eval_runtime": 86.8973,
|
| 995 |
+
"eval_samples_per_second": 15.835,
|
| 996 |
+
"eval_steps_per_second": 1.979,
|
| 997 |
+
"step": 940
|
| 998 |
+
},
|
| 999 |
+
{
|
| 1000 |
+
"entropy": 0.46456389091908934,
|
| 1001 |
+
"epoch": 2.3885429638854294,
|
| 1002 |
+
"grad_norm": 1.2000319957733154,
|
| 1003 |
+
"learning_rate": 0.00018999413588834105,
|
| 1004 |
+
"loss": 0.4084665775299072,
|
| 1005 |
+
"mean_token_accuracy": 0.8750658087432385,
|
| 1006 |
+
"num_tokens": 2239412.0,
|
| 1007 |
+
"step": 960
|
| 1008 |
+
},
|
| 1009 |
+
{
|
| 1010 |
+
"epoch": 2.3885429638854294,
|
| 1011 |
+
"eval_entropy": 0.4849439303195754,
|
| 1012 |
+
"eval_loss": 0.545662522315979,
|
| 1013 |
+
"eval_mean_token_accuracy": 0.8491013112456299,
|
| 1014 |
+
"eval_num_tokens": 2239412.0,
|
| 1015 |
+
"eval_runtime": 86.9049,
|
| 1016 |
+
"eval_samples_per_second": 15.833,
|
| 1017 |
+
"eval_steps_per_second": 1.979,
|
| 1018 |
+
"step": 960
|
| 1019 |
+
},
|
| 1020 |
+
{
|
| 1021 |
+
"entropy": 0.4857471022754908,
|
| 1022 |
+
"epoch": 2.4383561643835616,
|
| 1023 |
+
"grad_norm": 0.9696341753005981,
|
| 1024 |
+
"learning_rate": 0.0001891668789070541,
|
| 1025 |
+
"loss": 0.4149796962738037,
|
| 1026 |
+
"mean_token_accuracy": 0.8704176343977451,
|
| 1027 |
+
"num_tokens": 2286283.0,
|
| 1028 |
+
"step": 980
|
| 1029 |
+
},
|
| 1030 |
+
{
|
| 1031 |
+
"epoch": 2.4383561643835616,
|
| 1032 |
+
"eval_entropy": 0.4872790058684904,
|
| 1033 |
+
"eval_loss": 0.5412707924842834,
|
| 1034 |
+
"eval_mean_token_accuracy": 0.8509329602468846,
|
| 1035 |
+
"eval_num_tokens": 2286283.0,
|
| 1036 |
+
"eval_runtime": 86.7846,
|
| 1037 |
+
"eval_samples_per_second": 15.855,
|
| 1038 |
+
"eval_steps_per_second": 1.982,
|
| 1039 |
+
"step": 980
|
| 1040 |
+
},
|
| 1041 |
+
{
|
| 1042 |
+
"entropy": 0.4727417893707752,
|
| 1043 |
+
"epoch": 2.488169364881694,
|
| 1044 |
+
"grad_norm": 0.7852500677108765,
|
| 1045 |
+
"learning_rate": 0.0001883129646126818,
|
| 1046 |
+
"loss": 0.4142886161804199,
|
| 1047 |
+
"mean_token_accuracy": 0.8712429471313954,
|
| 1048 |
+
"num_tokens": 2333733.0,
|
| 1049 |
+
"step": 1000
|
| 1050 |
+
},
|
| 1051 |
+
{
|
| 1052 |
+
"epoch": 2.488169364881694,
|
| 1053 |
+
"eval_entropy": 0.5386548059624295,
|
| 1054 |
+
"eval_loss": 0.536101222038269,
|
| 1055 |
+
"eval_mean_token_accuracy": 0.8499491239009902,
|
| 1056 |
+
"eval_num_tokens": 2333733.0,
|
| 1057 |
+
"eval_runtime": 86.9501,
|
| 1058 |
+
"eval_samples_per_second": 15.825,
|
| 1059 |
+
"eval_steps_per_second": 1.978,
|
| 1060 |
+
"step": 1000
|
| 1061 |
+
},
|
| 1062 |
+
{
|
| 1063 |
+
"entropy": 0.4673406321555376,
|
| 1064 |
+
"epoch": 2.5379825653798256,
|
| 1065 |
+
"grad_norm": 0.7133921384811401,
|
| 1066 |
+
"learning_rate": 0.0001874326505341286,
|
| 1067 |
+
"loss": 0.40857529640197754,
|
| 1068 |
+
"mean_token_accuracy": 0.8747925907373428,
|
| 1069 |
+
"num_tokens": 2384270.0,
|
| 1070 |
+
"step": 1020
|
| 1071 |
+
},
|
| 1072 |
+
{
|
| 1073 |
+
"epoch": 2.5379825653798256,
|
| 1074 |
+
"eval_entropy": 0.495788364909416,
|
| 1075 |
+
"eval_loss": 0.5418923497200012,
|
| 1076 |
+
"eval_mean_token_accuracy": 0.851321972040243,
|
| 1077 |
+
"eval_num_tokens": 2384270.0,
|
| 1078 |
+
"eval_runtime": 86.7154,
|
| 1079 |
+
"eval_samples_per_second": 15.868,
|
| 1080 |
+
"eval_steps_per_second": 1.983,
|
| 1081 |
+
"step": 1020
|
| 1082 |
+
},
|
| 1083 |
+
{
|
| 1084 |
+
"entropy": 0.47599745728075504,
|
| 1085 |
+
"epoch": 2.587795765877958,
|
| 1086 |
+
"grad_norm": 0.8202953338623047,
|
| 1087 |
+
"learning_rate": 0.0001865262021621137,
|
| 1088 |
+
"loss": 0.40998234748840334,
|
| 1089 |
+
"mean_token_accuracy": 0.8758242674171924,
|
| 1090 |
+
"num_tokens": 2428036.0,
|
| 1091 |
+
"step": 1040
|
| 1092 |
+
},
|
| 1093 |
+
{
|
| 1094 |
+
"epoch": 2.587795765877958,
|
| 1095 |
+
"eval_entropy": 0.4887966953737791,
|
| 1096 |
+
"eval_loss": 0.5408804416656494,
|
| 1097 |
+
"eval_mean_token_accuracy": 0.8512661065473113,
|
| 1098 |
+
"eval_num_tokens": 2428036.0,
|
| 1099 |
+
"eval_runtime": 86.7869,
|
| 1100 |
+
"eval_samples_per_second": 15.855,
|
| 1101 |
+
"eval_steps_per_second": 1.982,
|
| 1102 |
+
"step": 1040
|
| 1103 |
+
},
|
| 1104 |
+
{
|
| 1105 |
+
"entropy": 0.4824396539479494,
|
| 1106 |
+
"epoch": 2.6376089663760895,
|
| 1107 |
+
"grad_norm": 0.6507360935211182,
|
| 1108 |
+
"learning_rate": 0.00018559389286910275,
|
| 1109 |
+
"loss": 0.4165764808654785,
|
| 1110 |
+
"mean_token_accuracy": 0.8722914069890976,
|
| 1111 |
+
"num_tokens": 2476815.0,
|
| 1112 |
+
"step": 1060
|
| 1113 |
+
},
|
| 1114 |
+
{
|
| 1115 |
+
"epoch": 2.6376089663760895,
|
| 1116 |
+
"eval_entropy": 0.4793398808254752,
|
| 1117 |
+
"eval_loss": 0.5326959490776062,
|
| 1118 |
+
"eval_mean_token_accuracy": 0.8534493650807891,
|
| 1119 |
+
"eval_num_tokens": 2476815.0,
|
| 1120 |
+
"eval_runtime": 86.9559,
|
| 1121 |
+
"eval_samples_per_second": 15.824,
|
| 1122 |
+
"eval_steps_per_second": 1.978,
|
| 1123 |
+
"step": 1060
|
| 1124 |
+
},
|
| 1125 |
+
{
|
| 1126 |
+
"entropy": 0.4605010639876127,
|
| 1127 |
+
"epoch": 2.6874221668742218,
|
| 1128 |
+
"grad_norm": 0.6740535497665405,
|
| 1129 |
+
"learning_rate": 0.00018463600382686253,
|
| 1130 |
+
"loss": 0.4123940944671631,
|
| 1131 |
+
"mean_token_accuracy": 0.8733638986945153,
|
| 1132 |
+
"num_tokens": 2527131.0,
|
| 1133 |
+
"step": 1080
|
| 1134 |
+
},
|
| 1135 |
+
{
|
| 1136 |
+
"epoch": 2.6874221668742218,
|
| 1137 |
+
"eval_entropy": 0.47902208583992584,
|
| 1138 |
+
"eval_loss": 0.5372340083122253,
|
| 1139 |
+
"eval_mean_token_accuracy": 0.851325950303743,
|
| 1140 |
+
"eval_num_tokens": 2527131.0,
|
| 1141 |
+
"eval_runtime": 86.9638,
|
| 1142 |
+
"eval_samples_per_second": 15.823,
|
| 1143 |
+
"eval_steps_per_second": 1.978,
|
| 1144 |
+
"step": 1080
|
| 1145 |
+
},
|
| 1146 |
+
{
|
| 1147 |
+
"entropy": 0.4872019402682781,
|
| 1148 |
+
"epoch": 2.7372353673723535,
|
| 1149 |
+
"grad_norm": 0.6994742155075073,
|
| 1150 |
+
"learning_rate": 0.0001836528239216632,
|
| 1151 |
+
"loss": 0.41599602699279786,
|
| 1152 |
+
"mean_token_accuracy": 0.872775862365961,
|
| 1153 |
+
"num_tokens": 2572537.0,
|
| 1154 |
+
"step": 1100
|
| 1155 |
+
},
|
| 1156 |
+
{
|
| 1157 |
+
"epoch": 2.7372353673723535,
|
| 1158 |
+
"eval_entropy": 0.4893243626453156,
|
| 1159 |
+
"eval_loss": 0.5327795743942261,
|
| 1160 |
+
"eval_mean_token_accuracy": 0.8537560302850812,
|
| 1161 |
+
"eval_num_tokens": 2572537.0,
|
| 1162 |
+
"eval_runtime": 86.823,
|
| 1163 |
+
"eval_samples_per_second": 15.848,
|
| 1164 |
+
"eval_steps_per_second": 1.981,
|
| 1165 |
+
"step": 1100
|
| 1166 |
+
},
|
| 1167 |
+
{
|
| 1168 |
+
"entropy": 0.4949610233306885,
|
| 1169 |
+
"epoch": 2.7870485678704857,
|
| 1170 |
+
"grad_norm": 0.9605912566184998,
|
| 1171 |
+
"learning_rate": 0.0001826446496671543,
|
| 1172 |
+
"loss": 0.4266993045806885,
|
| 1173 |
+
"mean_token_accuracy": 0.8688005246222019,
|
| 1174 |
+
"num_tokens": 2616047.0,
|
| 1175 |
+
"step": 1120
|
| 1176 |
+
},
|
| 1177 |
+
{
|
| 1178 |
+
"epoch": 2.7870485678704857,
|
| 1179 |
+
"eval_entropy": 0.5061517927882283,
|
| 1180 |
+
"eval_loss": 0.5356810092926025,
|
| 1181 |
+
"eval_mean_token_accuracy": 0.8524593568818514,
|
| 1182 |
+
"eval_num_tokens": 2616047.0,
|
| 1183 |
+
"eval_runtime": 86.8385,
|
| 1184 |
+
"eval_samples_per_second": 15.846,
|
| 1185 |
+
"eval_steps_per_second": 1.981,
|
| 1186 |
+
"step": 1120
|
| 1187 |
+
},
|
| 1188 |
+
{
|
| 1189 |
+
"entropy": 0.48401356525719164,
|
| 1190 |
+
"epoch": 2.8368617683686175,
|
| 1191 |
+
"grad_norm": 0.6332499980926514,
|
| 1192 |
+
"learning_rate": 0.00018161178511494022,
|
| 1193 |
+
"loss": 0.42131738662719725,
|
| 1194 |
+
"mean_token_accuracy": 0.8729447312653065,
|
| 1195 |
+
"num_tokens": 2664744.0,
|
| 1196 |
+
"step": 1140
|
| 1197 |
+
},
|
| 1198 |
+
{
|
| 1199 |
+
"epoch": 2.8368617683686175,
|
| 1200 |
+
"eval_entropy": 0.48792897060860035,
|
| 1201 |
+
"eval_loss": 0.5290402173995972,
|
| 1202 |
+
"eval_mean_token_accuracy": 0.853078076659247,
|
| 1203 |
+
"eval_num_tokens": 2664744.0,
|
| 1204 |
+
"eval_runtime": 86.7746,
|
| 1205 |
+
"eval_samples_per_second": 15.857,
|
| 1206 |
+
"eval_steps_per_second": 1.982,
|
| 1207 |
+
"step": 1140
|
| 1208 |
+
}
|
| 1209 |
+
],
|
| 1210 |
+
"logging_steps": 20,
|
| 1211 |
+
"max_steps": 4020,
|
| 1212 |
+
"num_input_tokens_seen": 0,
|
| 1213 |
+
"num_train_epochs": 10,
|
| 1214 |
+
"save_steps": 20,
|
| 1215 |
+
"stateful_callbacks": {
|
| 1216 |
+
"TrainerControl": {
|
| 1217 |
+
"args": {
|
| 1218 |
+
"should_epoch_stop": false,
|
| 1219 |
+
"should_evaluate": false,
|
| 1220 |
+
"should_log": false,
|
| 1221 |
+
"should_save": true,
|
| 1222 |
+
"should_training_stop": false
|
| 1223 |
+
},
|
| 1224 |
+
"attributes": {}
|
| 1225 |
+
}
|
| 1226 |
+
},
|
| 1227 |
+
"total_flos": 1.1277422592347136e+17,
|
| 1228 |
+
"train_batch_size": 4,
|
| 1229 |
+
"trial_name": null,
|
| 1230 |
+
"trial_params": null
|
| 1231 |
+
}
|
overgeneralisation_original_Swedish/Qwen3.5-4B-Base_overgeneralisation_splits_original_features_train_overgeneralisation_splits_original_features_test1/checkpoint-1160/README.md
ADDED
|
@@ -0,0 +1,209 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
---
|
| 2 |
+
base_model: Qwen/Qwen3.5-4B-Base
|
| 3 |
+
library_name: peft
|
| 4 |
+
pipeline_tag: text-generation
|
| 5 |
+
tags:
|
| 6 |
+
- base_model:adapter:Qwen/Qwen3.5-4B-Base
|
| 7 |
+
- lora
|
| 8 |
+
- sft
|
| 9 |
+
- transformers
|
| 10 |
+
- trl
|
| 11 |
+
---
|
| 12 |
+
|
| 13 |
+
# Model Card for Model ID
|
| 14 |
+
|
| 15 |
+
<!-- Provide a quick summary of what the model is/does. -->
|
| 16 |
+
|
| 17 |
+
|
| 18 |
+
|
| 19 |
+
## Model Details
|
| 20 |
+
|
| 21 |
+
### Model Description
|
| 22 |
+
|
| 23 |
+
<!-- Provide a longer summary of what this model is. -->
|
| 24 |
+
|
| 25 |
+
|
| 26 |
+
|
| 27 |
+
- **Developed by:** [More Information Needed]
|
| 28 |
+
- **Funded by [optional]:** [More Information Needed]
|
| 29 |
+
- **Shared by [optional]:** [More Information Needed]
|
| 30 |
+
- **Model type:** [More Information Needed]
|
| 31 |
+
- **Language(s) (NLP):** [More Information Needed]
|
| 32 |
+
- **License:** [More Information Needed]
|
| 33 |
+
- **Finetuned from model [optional]:** [More Information Needed]
|
| 34 |
+
|
| 35 |
+
### Model Sources [optional]
|
| 36 |
+
|
| 37 |
+
<!-- Provide the basic links for the model. -->
|
| 38 |
+
|
| 39 |
+
- **Repository:** [More Information Needed]
|
| 40 |
+
- **Paper [optional]:** [More Information Needed]
|
| 41 |
+
- **Demo [optional]:** [More Information Needed]
|
| 42 |
+
|
| 43 |
+
## Uses
|
| 44 |
+
|
| 45 |
+
<!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
|
| 46 |
+
|
| 47 |
+
### Direct Use
|
| 48 |
+
|
| 49 |
+
<!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
|
| 50 |
+
|
| 51 |
+
[More Information Needed]
|
| 52 |
+
|
| 53 |
+
### Downstream Use [optional]
|
| 54 |
+
|
| 55 |
+
<!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
|
| 56 |
+
|
| 57 |
+
[More Information Needed]
|
| 58 |
+
|
| 59 |
+
### Out-of-Scope Use
|
| 60 |
+
|
| 61 |
+
<!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
|
| 62 |
+
|
| 63 |
+
[More Information Needed]
|
| 64 |
+
|
| 65 |
+
## Bias, Risks, and Limitations
|
| 66 |
+
|
| 67 |
+
<!-- This section is meant to convey both technical and sociotechnical limitations. -->
|
| 68 |
+
|
| 69 |
+
[More Information Needed]
|
| 70 |
+
|
| 71 |
+
### Recommendations
|
| 72 |
+
|
| 73 |
+
<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
|
| 74 |
+
|
| 75 |
+
Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
|
| 76 |
+
|
| 77 |
+
## How to Get Started with the Model
|
| 78 |
+
|
| 79 |
+
Use the code below to get started with the model.
|
| 80 |
+
|
| 81 |
+
[More Information Needed]
|
| 82 |
+
|
| 83 |
+
## Training Details
|
| 84 |
+
|
| 85 |
+
### Training Data
|
| 86 |
+
|
| 87 |
+
<!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
|
| 88 |
+
|
| 89 |
+
[More Information Needed]
|
| 90 |
+
|
| 91 |
+
### Training Procedure
|
| 92 |
+
|
| 93 |
+
<!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
|
| 94 |
+
|
| 95 |
+
#### Preprocessing [optional]
|
| 96 |
+
|
| 97 |
+
[More Information Needed]
|
| 98 |
+
|
| 99 |
+
|
| 100 |
+
#### Training Hyperparameters
|
| 101 |
+
|
| 102 |
+
- **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
|
| 103 |
+
|
| 104 |
+
#### Speeds, Sizes, Times [optional]
|
| 105 |
+
|
| 106 |
+
<!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
|
| 107 |
+
|
| 108 |
+
[More Information Needed]
|
| 109 |
+
|
| 110 |
+
## Evaluation
|
| 111 |
+
|
| 112 |
+
<!-- This section describes the evaluation protocols and provides the results. -->
|
| 113 |
+
|
| 114 |
+
### Testing Data, Factors & Metrics
|
| 115 |
+
|
| 116 |
+
#### Testing Data
|
| 117 |
+
|
| 118 |
+
<!-- This should link to a Dataset Card if possible. -->
|
| 119 |
+
|
| 120 |
+
[More Information Needed]
|
| 121 |
+
|
| 122 |
+
#### Factors
|
| 123 |
+
|
| 124 |
+
<!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
|
| 125 |
+
|
| 126 |
+
[More Information Needed]
|
| 127 |
+
|
| 128 |
+
#### Metrics
|
| 129 |
+
|
| 130 |
+
<!-- These are the evaluation metrics being used, ideally with a description of why. -->
|
| 131 |
+
|
| 132 |
+
[More Information Needed]
|
| 133 |
+
|
| 134 |
+
### Results
|
| 135 |
+
|
| 136 |
+
[More Information Needed]
|
| 137 |
+
|
| 138 |
+
#### Summary
|
| 139 |
+
|
| 140 |
+
|
| 141 |
+
|
| 142 |
+
## Model Examination [optional]
|
| 143 |
+
|
| 144 |
+
<!-- Relevant interpretability work for the model goes here -->
|
| 145 |
+
|
| 146 |
+
[More Information Needed]
|
| 147 |
+
|
| 148 |
+
## Environmental Impact
|
| 149 |
+
|
| 150 |
+
<!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
|
| 151 |
+
|
| 152 |
+
Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
|
| 153 |
+
|
| 154 |
+
- **Hardware Type:** [More Information Needed]
|
| 155 |
+
- **Hours used:** [More Information Needed]
|
| 156 |
+
- **Cloud Provider:** [More Information Needed]
|
| 157 |
+
- **Compute Region:** [More Information Needed]
|
| 158 |
+
- **Carbon Emitted:** [More Information Needed]
|
| 159 |
+
|
| 160 |
+
## Technical Specifications [optional]
|
| 161 |
+
|
| 162 |
+
### Model Architecture and Objective
|
| 163 |
+
|
| 164 |
+
[More Information Needed]
|
| 165 |
+
|
| 166 |
+
### Compute Infrastructure
|
| 167 |
+
|
| 168 |
+
[More Information Needed]
|
| 169 |
+
|
| 170 |
+
#### Hardware
|
| 171 |
+
|
| 172 |
+
[More Information Needed]
|
| 173 |
+
|
| 174 |
+
#### Software
|
| 175 |
+
|
| 176 |
+
[More Information Needed]
|
| 177 |
+
|
| 178 |
+
## Citation [optional]
|
| 179 |
+
|
| 180 |
+
<!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
|
| 181 |
+
|
| 182 |
+
**BibTeX:**
|
| 183 |
+
|
| 184 |
+
[More Information Needed]
|
| 185 |
+
|
| 186 |
+
**APA:**
|
| 187 |
+
|
| 188 |
+
[More Information Needed]
|
| 189 |
+
|
| 190 |
+
## Glossary [optional]
|
| 191 |
+
|
| 192 |
+
<!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
|
| 193 |
+
|
| 194 |
+
[More Information Needed]
|
| 195 |
+
|
| 196 |
+
## More Information [optional]
|
| 197 |
+
|
| 198 |
+
[More Information Needed]
|
| 199 |
+
|
| 200 |
+
## Model Card Authors [optional]
|
| 201 |
+
|
| 202 |
+
[More Information Needed]
|
| 203 |
+
|
| 204 |
+
## Model Card Contact
|
| 205 |
+
|
| 206 |
+
[More Information Needed]
|
| 207 |
+
### Framework versions
|
| 208 |
+
|
| 209 |
+
- PEFT 0.18.1
|
overgeneralisation_original_Swedish/Qwen3.5-4B-Base_overgeneralisation_splits_original_features_train_overgeneralisation_splits_original_features_test1/checkpoint-1160/adapter_config.json
ADDED
|
@@ -0,0 +1,46 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
{
|
| 2 |
+
"alora_invocation_tokens": null,
|
| 3 |
+
"alpha_pattern": {},
|
| 4 |
+
"arrow_config": null,
|
| 5 |
+
"auto_mapping": null,
|
| 6 |
+
"base_model_name_or_path": "Qwen/Qwen3.5-4B-Base",
|
| 7 |
+
"bias": "none",
|
| 8 |
+
"corda_config": null,
|
| 9 |
+
"ensure_weight_tying": false,
|
| 10 |
+
"eva_config": null,
|
| 11 |
+
"exclude_modules": null,
|
| 12 |
+
"fan_in_fan_out": false,
|
| 13 |
+
"inference_mode": true,
|
| 14 |
+
"init_lora_weights": true,
|
| 15 |
+
"layer_replication": null,
|
| 16 |
+
"layers_pattern": null,
|
| 17 |
+
"layers_to_transform": null,
|
| 18 |
+
"loftq_config": {},
|
| 19 |
+
"lora_alpha": 256,
|
| 20 |
+
"lora_bias": false,
|
| 21 |
+
"lora_dropout": 0.0005183818805460705,
|
| 22 |
+
"megatron_config": null,
|
| 23 |
+
"megatron_core": "megatron.core",
|
| 24 |
+
"modules_to_save": null,
|
| 25 |
+
"peft_type": "LORA",
|
| 26 |
+
"peft_version": "0.18.1",
|
| 27 |
+
"qalora_group_size": 16,
|
| 28 |
+
"r": 128,
|
| 29 |
+
"rank_pattern": {},
|
| 30 |
+
"revision": null,
|
| 31 |
+
"target_modules": [
|
| 32 |
+
"up_proj",
|
| 33 |
+
"q_proj",
|
| 34 |
+
"o_proj",
|
| 35 |
+
"v_proj",
|
| 36 |
+
"k_proj",
|
| 37 |
+
"gate_proj",
|
| 38 |
+
"down_proj"
|
| 39 |
+
],
|
| 40 |
+
"target_parameters": null,
|
| 41 |
+
"task_type": "CAUSAL_LM",
|
| 42 |
+
"trainable_token_indices": null,
|
| 43 |
+
"use_dora": false,
|
| 44 |
+
"use_qalora": false,
|
| 45 |
+
"use_rslora": false
|
| 46 |
+
}
|
overgeneralisation_original_Swedish/Qwen3.5-4B-Base_overgeneralisation_splits_original_features_train_overgeneralisation_splits_original_features_test1/checkpoint-1160/chat_template.jinja
ADDED
|
@@ -0,0 +1,154 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
{%- set image_count = namespace(value=0) %}
|
| 2 |
+
{%- set video_count = namespace(value=0) %}
|
| 3 |
+
{%- macro render_content(content, do_vision_count, is_system_content=false) %}
|
| 4 |
+
{%- if content is string %}
|
| 5 |
+
{{- content }}
|
| 6 |
+
{%- elif content is iterable and content is not mapping %}
|
| 7 |
+
{%- for item in content %}
|
| 8 |
+
{%- if 'image' in item or 'image_url' in item or item.type == 'image' %}
|
| 9 |
+
{%- if is_system_content %}
|
| 10 |
+
{{- raise_exception('System message cannot contain images.') }}
|
| 11 |
+
{%- endif %}
|
| 12 |
+
{%- if do_vision_count %}
|
| 13 |
+
{%- set image_count.value = image_count.value + 1 %}
|
| 14 |
+
{%- endif %}
|
| 15 |
+
{%- if add_vision_id %}
|
| 16 |
+
{{- 'Picture ' ~ image_count.value ~ ': ' }}
|
| 17 |
+
{%- endif %}
|
| 18 |
+
{{- '<|vision_start|><|image_pad|><|vision_end|>' }}
|
| 19 |
+
{%- elif 'video' in item or item.type == 'video' %}
|
| 20 |
+
{%- if is_system_content %}
|
| 21 |
+
{{- raise_exception('System message cannot contain videos.') }}
|
| 22 |
+
{%- endif %}
|
| 23 |
+
{%- if do_vision_count %}
|
| 24 |
+
{%- set video_count.value = video_count.value + 1 %}
|
| 25 |
+
{%- endif %}
|
| 26 |
+
{%- if add_vision_id %}
|
| 27 |
+
{{- 'Video ' ~ video_count.value ~ ': ' }}
|
| 28 |
+
{%- endif %}
|
| 29 |
+
{{- '<|vision_start|><|video_pad|><|vision_end|>' }}
|
| 30 |
+
{%- elif 'text' in item %}
|
| 31 |
+
{{- item.text }}
|
| 32 |
+
{%- else %}
|
| 33 |
+
{{- raise_exception('Unexpected item type in content.') }}
|
| 34 |
+
{%- endif %}
|
| 35 |
+
{%- endfor %}
|
| 36 |
+
{%- elif content is none or content is undefined %}
|
| 37 |
+
{{- '' }}
|
| 38 |
+
{%- else %}
|
| 39 |
+
{{- raise_exception('Unexpected content type.') }}
|
| 40 |
+
{%- endif %}
|
| 41 |
+
{%- endmacro %}
|
| 42 |
+
{%- if not messages %}
|
| 43 |
+
{{- raise_exception('No messages provided.') }}
|
| 44 |
+
{%- endif %}
|
| 45 |
+
{%- if tools and tools is iterable and tools is not mapping %}
|
| 46 |
+
{{- '<|im_start|>system\n' }}
|
| 47 |
+
{{- "# Tools\n\nYou have access to the following functions:\n\n<tools>" }}
|
| 48 |
+
{%- for tool in tools %}
|
| 49 |
+
{{- "\n" }}
|
| 50 |
+
{{- tool | tojson }}
|
| 51 |
+
{%- endfor %}
|
| 52 |
+
{{- "\n</tools>" }}
|
| 53 |
+
{{- '\n\nIf you choose to call a function ONLY reply in the following format with NO suffix:\n\n<tool_call>\n<function=example_function_name>\n<parameter=example_parameter_1>\nvalue_1\n</parameter>\n<parameter=example_parameter_2>\nThis is the value for the second parameter\nthat can span\nmultiple lines\n</parameter>\n</function>\n</tool_call>\n\n<IMPORTANT>\nReminder:\n- Function calls MUST follow the specified format: an inner <function=...></function> block must be nested within <tool_call></tool_call> XML tags\n- Required parameters MUST be specified\n- You may provide optional reasoning for your function call in natural language BEFORE the function call, but NOT after\n- If there is no function call available, answer the question like normal with your current knowledge and do not tell the user about function calls\n</IMPORTANT>' }}
|
| 54 |
+
{%- if messages[0].role == 'system' %}
|
| 55 |
+
{%- set content = render_content(messages[0].content, false, true)|trim %}
|
| 56 |
+
{%- if content %}
|
| 57 |
+
{{- '\n\n' + content }}
|
| 58 |
+
{%- endif %}
|
| 59 |
+
{%- endif %}
|
| 60 |
+
{{- '<|im_end|>\n' }}
|
| 61 |
+
{%- else %}
|
| 62 |
+
{%- if messages[0].role == 'system' %}
|
| 63 |
+
{%- set content = render_content(messages[0].content, false, true)|trim %}
|
| 64 |
+
{{- '<|im_start|>system\n' + content + '<|im_end|>\n' }}
|
| 65 |
+
{%- endif %}
|
| 66 |
+
{%- endif %}
|
| 67 |
+
{%- set ns = namespace(multi_step_tool=true, last_query_index=messages|length - 1) %}
|
| 68 |
+
{%- for message in messages[::-1] %}
|
| 69 |
+
{%- set index = (messages|length - 1) - loop.index0 %}
|
| 70 |
+
{%- if ns.multi_step_tool and message.role == "user" %}
|
| 71 |
+
{%- set content = render_content(message.content, false)|trim %}
|
| 72 |
+
{%- if not(content.startswith('<tool_response>') and content.endswith('</tool_response>')) %}
|
| 73 |
+
{%- set ns.multi_step_tool = false %}
|
| 74 |
+
{%- set ns.last_query_index = index %}
|
| 75 |
+
{%- endif %}
|
| 76 |
+
{%- endif %}
|
| 77 |
+
{%- endfor %}
|
| 78 |
+
{%- if ns.multi_step_tool %}
|
| 79 |
+
{{- raise_exception('No user query found in messages.') }}
|
| 80 |
+
{%- endif %}
|
| 81 |
+
{%- for message in messages %}
|
| 82 |
+
{%- set content = render_content(message.content, true)|trim %}
|
| 83 |
+
{%- if message.role == "system" %}
|
| 84 |
+
{%- if not loop.first %}
|
| 85 |
+
{{- raise_exception('System message must be at the beginning.') }}
|
| 86 |
+
{%- endif %}
|
| 87 |
+
{%- elif message.role == "user" %}
|
| 88 |
+
{{- '<|im_start|>' + message.role + '\n' + content + '<|im_end|>' + '\n' }}
|
| 89 |
+
{%- elif message.role == "assistant" %}
|
| 90 |
+
{%- set reasoning_content = '' %}
|
| 91 |
+
{%- if message.reasoning_content is string %}
|
| 92 |
+
{%- set reasoning_content = message.reasoning_content %}
|
| 93 |
+
{%- else %}
|
| 94 |
+
{%- if '</think>' in content %}
|
| 95 |
+
{%- set reasoning_content = content.split('</think>')[0].rstrip('\n').split('<think>')[-1].lstrip('\n') %}
|
| 96 |
+
{%- set content = content.split('</think>')[-1].lstrip('\n') %}
|
| 97 |
+
{%- endif %}
|
| 98 |
+
{%- endif %}
|
| 99 |
+
{%- set reasoning_content = reasoning_content|trim %}
|
| 100 |
+
{%- if loop.index0 > ns.last_query_index %}
|
| 101 |
+
{{- '<|im_start|>' + message.role + '\n<think>\n' + reasoning_content + '\n</think>\n\n' + content }}
|
| 102 |
+
{%- else %}
|
| 103 |
+
{{- '<|im_start|>' + message.role + '\n' + content }}
|
| 104 |
+
{%- endif %}
|
| 105 |
+
{%- if message.tool_calls and message.tool_calls is iterable and message.tool_calls is not mapping %}
|
| 106 |
+
{%- for tool_call in message.tool_calls %}
|
| 107 |
+
{%- if tool_call.function is defined %}
|
| 108 |
+
{%- set tool_call = tool_call.function %}
|
| 109 |
+
{%- endif %}
|
| 110 |
+
{%- if loop.first %}
|
| 111 |
+
{%- if content|trim %}
|
| 112 |
+
{{- '\n\n<tool_call>\n<function=' + tool_call.name + '>\n' }}
|
| 113 |
+
{%- else %}
|
| 114 |
+
{{- '<tool_call>\n<function=' + tool_call.name + '>\n' }}
|
| 115 |
+
{%- endif %}
|
| 116 |
+
{%- else %}
|
| 117 |
+
{{- '\n<tool_call>\n<function=' + tool_call.name + '>\n' }}
|
| 118 |
+
{%- endif %}
|
| 119 |
+
{%- if tool_call.arguments is defined %}
|
| 120 |
+
{%- for args_name, args_value in tool_call.arguments|items %}
|
| 121 |
+
{{- '<parameter=' + args_name + '>\n' }}
|
| 122 |
+
{%- set args_value = args_value | tojson | safe if args_value is mapping or (args_value is sequence and args_value is not string) else args_value | string %}
|
| 123 |
+
{{- args_value }}
|
| 124 |
+
{{- '\n</parameter>\n' }}
|
| 125 |
+
{%- endfor %}
|
| 126 |
+
{%- endif %}
|
| 127 |
+
{{- '</function>\n</tool_call>' }}
|
| 128 |
+
{%- endfor %}
|
| 129 |
+
{%- endif %}
|
| 130 |
+
{{- '<|im_end|>\n' }}
|
| 131 |
+
{%- elif message.role == "tool" %}
|
| 132 |
+
{%- if loop.previtem and loop.previtem.role != "tool" %}
|
| 133 |
+
{{- '<|im_start|>user' }}
|
| 134 |
+
{%- endif %}
|
| 135 |
+
{{- '\n<tool_response>\n' }}
|
| 136 |
+
{{- content }}
|
| 137 |
+
{{- '\n</tool_response>' }}
|
| 138 |
+
{%- if not loop.last and loop.nextitem.role != "tool" %}
|
| 139 |
+
{{- '<|im_end|>\n' }}
|
| 140 |
+
{%- elif loop.last %}
|
| 141 |
+
{{- '<|im_end|>\n' }}
|
| 142 |
+
{%- endif %}
|
| 143 |
+
{%- else %}
|
| 144 |
+
{{- raise_exception('Unexpected message role.') }}
|
| 145 |
+
{%- endif %}
|
| 146 |
+
{%- endfor %}
|
| 147 |
+
{%- if add_generation_prompt %}
|
| 148 |
+
{{- '<|im_start|>assistant\n' }}
|
| 149 |
+
{%- if enable_thinking is defined and enable_thinking is false %}
|
| 150 |
+
{{- '<think>\n\n</think>\n\n' }}
|
| 151 |
+
{%- else %}
|
| 152 |
+
{{- '<think>\n' }}
|
| 153 |
+
{%- endif %}
|
| 154 |
+
{%- endif %}
|
overgeneralisation_original_Swedish/Qwen3.5-4B-Base_overgeneralisation_splits_original_features_train_overgeneralisation_splits_original_features_test1/checkpoint-1160/tokenizer_config.json
ADDED
|
@@ -0,0 +1,31 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
{
|
| 2 |
+
"add_prefix_space": false,
|
| 3 |
+
"audio_bos_token": "<|audio_start|>",
|
| 4 |
+
"audio_eos_token": "<|audio_end|>",
|
| 5 |
+
"audio_token": "<|audio_pad|>",
|
| 6 |
+
"backend": "tokenizers",
|
| 7 |
+
"bos_token": null,
|
| 8 |
+
"clean_up_tokenization_spaces": false,
|
| 9 |
+
"eos_token": "<|endoftext|>",
|
| 10 |
+
"errors": "replace",
|
| 11 |
+
"image_token": "<|image_pad|>",
|
| 12 |
+
"is_local": false,
|
| 13 |
+
"model_max_length": 262144,
|
| 14 |
+
"model_specific_special_tokens": {
|
| 15 |
+
"audio_bos_token": "<|audio_start|>",
|
| 16 |
+
"audio_eos_token": "<|audio_end|>",
|
| 17 |
+
"audio_token": "<|audio_pad|>",
|
| 18 |
+
"image_token": "<|image_pad|>",
|
| 19 |
+
"video_token": "<|video_pad|>",
|
| 20 |
+
"vision_bos_token": "<|vision_start|>",
|
| 21 |
+
"vision_eos_token": "<|vision_end|>"
|
| 22 |
+
},
|
| 23 |
+
"pad_token": "<|endoftext|>",
|
| 24 |
+
"pretokenize_regex": "(?i:'s|'t|'re|'ve|'m|'ll|'d)|[^\\r\\n\\p{L}\\p{N}]?[\\p{L}\\p{M}]+|\\p{N}| ?[^\\s\\p{L}\\p{M}\\p{N}]+[\\r\\n]*|\\s*[\\r\\n]+|\\s+(?!\\S)|\\s+",
|
| 25 |
+
"split_special_tokens": false,
|
| 26 |
+
"tokenizer_class": "TokenizersBackend",
|
| 27 |
+
"unk_token": null,
|
| 28 |
+
"video_token": "<|video_pad|>",
|
| 29 |
+
"vision_bos_token": "<|vision_start|>",
|
| 30 |
+
"vision_eos_token": "<|vision_end|>"
|
| 31 |
+
}
|
overgeneralisation_original_Swedish/Qwen3.5-4B-Base_overgeneralisation_splits_original_features_train_overgeneralisation_splits_original_features_test1/checkpoint-1160/trainer_state.json
ADDED
|
@@ -0,0 +1,1252 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
{
|
| 2 |
+
"best_global_step": null,
|
| 3 |
+
"best_metric": null,
|
| 4 |
+
"best_model_checkpoint": null,
|
| 5 |
+
"epoch": 2.8866749688667497,
|
| 6 |
+
"eval_steps": 20,
|
| 7 |
+
"global_step": 1160,
|
| 8 |
+
"is_hyper_param_search": false,
|
| 9 |
+
"is_local_process_zero": true,
|
| 10 |
+
"is_world_process_zero": true,
|
| 11 |
+
"log_history": [
|
| 12 |
+
{
|
| 13 |
+
"entropy": 1.9784346982836722,
|
| 14 |
+
"epoch": 0.049813200498132,
|
| 15 |
+
"grad_norm": 3.0229668617248535,
|
| 16 |
+
"learning_rate": 9.526142962415369e-06,
|
| 17 |
+
"loss": 1.7360023498535155,
|
| 18 |
+
"mean_token_accuracy": 0.6449888605624438,
|
| 19 |
+
"num_tokens": 46794.0,
|
| 20 |
+
"step": 20
|
| 21 |
+
},
|
| 22 |
+
{
|
| 23 |
+
"epoch": 0.049813200498132,
|
| 24 |
+
"eval_entropy": 1.41506897571475,
|
| 25 |
+
"eval_loss": 1.1876318454742432,
|
| 26 |
+
"eval_mean_token_accuracy": 0.734131895525511,
|
| 27 |
+
"eval_num_tokens": 46794.0,
|
| 28 |
+
"eval_runtime": 87.8071,
|
| 29 |
+
"eval_samples_per_second": 15.671,
|
| 30 |
+
"eval_steps_per_second": 1.959,
|
| 31 |
+
"step": 20
|
| 32 |
+
},
|
| 33 |
+
{
|
| 34 |
+
"entropy": 1.049924298375845,
|
| 35 |
+
"epoch": 0.099626400996264,
|
| 36 |
+
"grad_norm": 1.5795097351074219,
|
| 37 |
+
"learning_rate": 1.9553661870221022e-05,
|
| 38 |
+
"loss": 0.8944448471069336,
|
| 39 |
+
"mean_token_accuracy": 0.7748479396104813,
|
| 40 |
+
"num_tokens": 90754.0,
|
| 41 |
+
"step": 40
|
| 42 |
+
},
|
| 43 |
+
{
|
| 44 |
+
"epoch": 0.099626400996264,
|
| 45 |
+
"eval_entropy": 0.7996658658565476,
|
| 46 |
+
"eval_loss": 0.7202735543251038,
|
| 47 |
+
"eval_mean_token_accuracy": 0.8070558306089667,
|
| 48 |
+
"eval_num_tokens": 90754.0,
|
| 49 |
+
"eval_runtime": 86.9199,
|
| 50 |
+
"eval_samples_per_second": 15.831,
|
| 51 |
+
"eval_steps_per_second": 1.979,
|
| 52 |
+
"step": 40
|
| 53 |
+
},
|
| 54 |
+
{
|
| 55 |
+
"entropy": 0.7734908878803253,
|
| 56 |
+
"epoch": 0.149439601494396,
|
| 57 |
+
"grad_norm": 1.3136248588562012,
|
| 58 |
+
"learning_rate": 2.9581180778026673e-05,
|
| 59 |
+
"loss": 0.6780608654022217,
|
| 60 |
+
"mean_token_accuracy": 0.8168170280754566,
|
| 61 |
+
"num_tokens": 137472.0,
|
| 62 |
+
"step": 60
|
| 63 |
+
},
|
| 64 |
+
{
|
| 65 |
+
"epoch": 0.149439601494396,
|
| 66 |
+
"eval_entropy": 0.7119324009778888,
|
| 67 |
+
"eval_loss": 0.6554311513900757,
|
| 68 |
+
"eval_mean_token_accuracy": 0.8215604798738346,
|
| 69 |
+
"eval_num_tokens": 137472.0,
|
| 70 |
+
"eval_runtime": 86.8692,
|
| 71 |
+
"eval_samples_per_second": 15.84,
|
| 72 |
+
"eval_steps_per_second": 1.98,
|
| 73 |
+
"step": 60
|
| 74 |
+
},
|
| 75 |
+
{
|
| 76 |
+
"entropy": 0.7071127541363239,
|
| 77 |
+
"epoch": 0.199252801992528,
|
| 78 |
+
"grad_norm": 1.387060284614563,
|
| 79 |
+
"learning_rate": 3.960869968583232e-05,
|
| 80 |
+
"loss": 0.6382100582122803,
|
| 81 |
+
"mean_token_accuracy": 0.8229366384446621,
|
| 82 |
+
"num_tokens": 187408.0,
|
| 83 |
+
"step": 80
|
| 84 |
+
},
|
| 85 |
+
{
|
| 86 |
+
"epoch": 0.199252801992528,
|
| 87 |
+
"eval_entropy": 0.6883931482254073,
|
| 88 |
+
"eval_loss": 0.625065803527832,
|
| 89 |
+
"eval_mean_token_accuracy": 0.828940509710201,
|
| 90 |
+
"eval_num_tokens": 187408.0,
|
| 91 |
+
"eval_runtime": 86.662,
|
| 92 |
+
"eval_samples_per_second": 15.878,
|
| 93 |
+
"eval_steps_per_second": 1.985,
|
| 94 |
+
"step": 80
|
| 95 |
+
},
|
| 96 |
+
{
|
| 97 |
+
"entropy": 0.6800824083387852,
|
| 98 |
+
"epoch": 0.24906600249066002,
|
| 99 |
+
"grad_norm": 0.9892916679382324,
|
| 100 |
+
"learning_rate": 4.963621859363797e-05,
|
| 101 |
+
"loss": 0.6011715888977051,
|
| 102 |
+
"mean_token_accuracy": 0.8323964163661003,
|
| 103 |
+
"num_tokens": 234197.0,
|
| 104 |
+
"step": 100
|
| 105 |
+
},
|
| 106 |
+
{
|
| 107 |
+
"epoch": 0.24906600249066002,
|
| 108 |
+
"eval_entropy": 0.6840810470802839,
|
| 109 |
+
"eval_loss": 0.6037028431892395,
|
| 110 |
+
"eval_mean_token_accuracy": 0.8309669033732525,
|
| 111 |
+
"eval_num_tokens": 234197.0,
|
| 112 |
+
"eval_runtime": 86.4637,
|
| 113 |
+
"eval_samples_per_second": 15.914,
|
| 114 |
+
"eval_steps_per_second": 1.989,
|
| 115 |
+
"step": 100
|
| 116 |
+
},
|
| 117 |
+
{
|
| 118 |
+
"entropy": 0.6776216626167297,
|
| 119 |
+
"epoch": 0.298879202988792,
|
| 120 |
+
"grad_norm": 0.8918434977531433,
|
| 121 |
+
"learning_rate": 5.9663737501443624e-05,
|
| 122 |
+
"loss": 0.5991742610931396,
|
| 123 |
+
"mean_token_accuracy": 0.8300838828086853,
|
| 124 |
+
"num_tokens": 281241.0,
|
| 125 |
+
"step": 120
|
| 126 |
+
},
|
| 127 |
+
{
|
| 128 |
+
"epoch": 0.298879202988792,
|
| 129 |
+
"eval_entropy": 0.690427724705186,
|
| 130 |
+
"eval_loss": 0.5939701795578003,
|
| 131 |
+
"eval_mean_token_accuracy": 0.8345950186945671,
|
| 132 |
+
"eval_num_tokens": 281241.0,
|
| 133 |
+
"eval_runtime": 86.6626,
|
| 134 |
+
"eval_samples_per_second": 15.878,
|
| 135 |
+
"eval_steps_per_second": 1.985,
|
| 136 |
+
"step": 120
|
| 137 |
+
},
|
| 138 |
+
{
|
| 139 |
+
"entropy": 0.6709842771291733,
|
| 140 |
+
"epoch": 0.34869240348692404,
|
| 141 |
+
"grad_norm": 0.9135531187057495,
|
| 142 |
+
"learning_rate": 6.969125640924927e-05,
|
| 143 |
+
"loss": 0.5914147377014161,
|
| 144 |
+
"mean_token_accuracy": 0.8314545609056949,
|
| 145 |
+
"num_tokens": 327393.0,
|
| 146 |
+
"step": 140
|
| 147 |
+
},
|
| 148 |
+
{
|
| 149 |
+
"epoch": 0.34869240348692404,
|
| 150 |
+
"eval_entropy": 0.6584504666023476,
|
| 151 |
+
"eval_loss": 0.5849721431732178,
|
| 152 |
+
"eval_mean_token_accuracy": 0.8357757236375365,
|
| 153 |
+
"eval_num_tokens": 327393.0,
|
| 154 |
+
"eval_runtime": 86.3262,
|
| 155 |
+
"eval_samples_per_second": 15.94,
|
| 156 |
+
"eval_steps_per_second": 1.992,
|
| 157 |
+
"step": 140
|
| 158 |
+
},
|
| 159 |
+
{
|
| 160 |
+
"entropy": 0.6524647936224938,
|
| 161 |
+
"epoch": 0.398505603985056,
|
| 162 |
+
"grad_norm": 0.8651587963104248,
|
| 163 |
+
"learning_rate": 7.971877531705493e-05,
|
| 164 |
+
"loss": 0.5710843563079834,
|
| 165 |
+
"mean_token_accuracy": 0.8396127380430698,
|
| 166 |
+
"num_tokens": 373834.0,
|
| 167 |
+
"step": 160
|
| 168 |
+
},
|
| 169 |
+
{
|
| 170 |
+
"epoch": 0.398505603985056,
|
| 171 |
+
"eval_entropy": 0.6283470298661742,
|
| 172 |
+
"eval_loss": 0.5738973617553711,
|
| 173 |
+
"eval_mean_token_accuracy": 0.8379981181649274,
|
| 174 |
+
"eval_num_tokens": 373834.0,
|
| 175 |
+
"eval_runtime": 86.5619,
|
| 176 |
+
"eval_samples_per_second": 15.896,
|
| 177 |
+
"eval_steps_per_second": 1.987,
|
| 178 |
+
"step": 160
|
| 179 |
+
},
|
| 180 |
+
{
|
| 181 |
+
"entropy": 0.6450445972383022,
|
| 182 |
+
"epoch": 0.44831880448318806,
|
| 183 |
+
"grad_norm": 0.8661723732948303,
|
| 184 |
+
"learning_rate": 8.974629422486058e-05,
|
| 185 |
+
"loss": 0.5677794933319091,
|
| 186 |
+
"mean_token_accuracy": 0.8389350369572639,
|
| 187 |
+
"num_tokens": 422572.0,
|
| 188 |
+
"step": 180
|
| 189 |
+
},
|
| 190 |
+
{
|
| 191 |
+
"epoch": 0.44831880448318806,
|
| 192 |
+
"eval_entropy": 0.6142613257086554,
|
| 193 |
+
"eval_loss": 0.5698265433311462,
|
| 194 |
+
"eval_mean_token_accuracy": 0.8388577273418737,
|
| 195 |
+
"eval_num_tokens": 422572.0,
|
| 196 |
+
"eval_runtime": 86.4443,
|
| 197 |
+
"eval_samples_per_second": 15.918,
|
| 198 |
+
"eval_steps_per_second": 1.99,
|
| 199 |
+
"step": 180
|
| 200 |
+
},
|
| 201 |
+
{
|
| 202 |
+
"entropy": 0.6448334597051144,
|
| 203 |
+
"epoch": 0.49813200498132004,
|
| 204 |
+
"grad_norm": 0.9662242531776428,
|
| 205 |
+
"learning_rate": 9.977381313266624e-05,
|
| 206 |
+
"loss": 0.581433916091919,
|
| 207 |
+
"mean_token_accuracy": 0.8387043006718159,
|
| 208 |
+
"num_tokens": 471879.0,
|
| 209 |
+
"step": 200
|
| 210 |
+
},
|
| 211 |
+
{
|
| 212 |
+
"epoch": 0.49813200498132004,
|
| 213 |
+
"eval_entropy": 0.6154296522916749,
|
| 214 |
+
"eval_loss": 0.5660303831100464,
|
| 215 |
+
"eval_mean_token_accuracy": 0.8412494766850804,
|
| 216 |
+
"eval_num_tokens": 471879.0,
|
| 217 |
+
"eval_runtime": 86.3063,
|
| 218 |
+
"eval_samples_per_second": 15.943,
|
| 219 |
+
"eval_steps_per_second": 1.993,
|
| 220 |
+
"step": 200
|
| 221 |
+
},
|
| 222 |
+
{
|
| 223 |
+
"entropy": 0.6376728117465973,
|
| 224 |
+
"epoch": 0.547945205479452,
|
| 225 |
+
"grad_norm": 0.7618638873100281,
|
| 226 |
+
"learning_rate": 0.00010980133204047189,
|
| 227 |
+
"loss": 0.5678351402282715,
|
| 228 |
+
"mean_token_accuracy": 0.8404546812176704,
|
| 229 |
+
"num_tokens": 520984.0,
|
| 230 |
+
"step": 220
|
| 231 |
+
},
|
| 232 |
+
{
|
| 233 |
+
"epoch": 0.547945205479452,
|
| 234 |
+
"eval_entropy": 0.6181817033956217,
|
| 235 |
+
"eval_loss": 0.5663750171661377,
|
| 236 |
+
"eval_mean_token_accuracy": 0.8388350962899452,
|
| 237 |
+
"eval_num_tokens": 520984.0,
|
| 238 |
+
"eval_runtime": 86.5904,
|
| 239 |
+
"eval_samples_per_second": 15.891,
|
| 240 |
+
"eval_steps_per_second": 1.986,
|
| 241 |
+
"step": 220
|
| 242 |
+
},
|
| 243 |
+
{
|
| 244 |
+
"entropy": 0.6303176879882812,
|
| 245 |
+
"epoch": 0.597758405977584,
|
| 246 |
+
"grad_norm": 0.7571695446968079,
|
| 247 |
+
"learning_rate": 0.00011982885094827753,
|
| 248 |
+
"loss": 0.5502778053283691,
|
| 249 |
+
"mean_token_accuracy": 0.8429657347500324,
|
| 250 |
+
"num_tokens": 566596.0,
|
| 251 |
+
"step": 240
|
| 252 |
+
},
|
| 253 |
+
{
|
| 254 |
+
"epoch": 0.597758405977584,
|
| 255 |
+
"eval_entropy": 0.6252533817707107,
|
| 256 |
+
"eval_loss": 0.5570284128189087,
|
| 257 |
+
"eval_mean_token_accuracy": 0.8427327847064927,
|
| 258 |
+
"eval_num_tokens": 566596.0,
|
| 259 |
+
"eval_runtime": 86.4157,
|
| 260 |
+
"eval_samples_per_second": 15.923,
|
| 261 |
+
"eval_steps_per_second": 1.99,
|
| 262 |
+
"step": 240
|
| 263 |
+
},
|
| 264 |
+
{
|
| 265 |
+
"entropy": 0.6202544964849949,
|
| 266 |
+
"epoch": 0.6475716064757161,
|
| 267 |
+
"grad_norm": 0.6447190642356873,
|
| 268 |
+
"learning_rate": 0.00012985636985608318,
|
| 269 |
+
"loss": 0.5485352993011474,
|
| 270 |
+
"mean_token_accuracy": 0.844165726006031,
|
| 271 |
+
"num_tokens": 613603.0,
|
| 272 |
+
"step": 260
|
| 273 |
+
},
|
| 274 |
+
{
|
| 275 |
+
"epoch": 0.6475716064757161,
|
| 276 |
+
"eval_entropy": 0.6441633552312851,
|
| 277 |
+
"eval_loss": 0.5606644153594971,
|
| 278 |
+
"eval_mean_token_accuracy": 0.842403513054515,
|
| 279 |
+
"eval_num_tokens": 613603.0,
|
| 280 |
+
"eval_runtime": 86.6343,
|
| 281 |
+
"eval_samples_per_second": 15.883,
|
| 282 |
+
"eval_steps_per_second": 1.985,
|
| 283 |
+
"step": 260
|
| 284 |
+
},
|
| 285 |
+
{
|
| 286 |
+
"entropy": 0.6306711677461863,
|
| 287 |
+
"epoch": 0.6973848069738481,
|
| 288 |
+
"grad_norm": 0.7869907021522522,
|
| 289 |
+
"learning_rate": 0.00013988388876388883,
|
| 290 |
+
"loss": 0.5579307556152344,
|
| 291 |
+
"mean_token_accuracy": 0.841247134655714,
|
| 292 |
+
"num_tokens": 658565.0,
|
| 293 |
+
"step": 280
|
| 294 |
+
},
|
| 295 |
+
{
|
| 296 |
+
"epoch": 0.6973848069738481,
|
| 297 |
+
"eval_entropy": 0.6263934678809587,
|
| 298 |
+
"eval_loss": 0.5559113025665283,
|
| 299 |
+
"eval_mean_token_accuracy": 0.8427334743183713,
|
| 300 |
+
"eval_num_tokens": 658565.0,
|
| 301 |
+
"eval_runtime": 86.6403,
|
| 302 |
+
"eval_samples_per_second": 15.882,
|
| 303 |
+
"eval_steps_per_second": 1.985,
|
| 304 |
+
"step": 280
|
| 305 |
+
},
|
| 306 |
+
{
|
| 307 |
+
"entropy": 0.6385872110724449,
|
| 308 |
+
"epoch": 0.7471980074719801,
|
| 309 |
+
"grad_norm": 0.6679229736328125,
|
| 310 |
+
"learning_rate": 0.0001499114076716945,
|
| 311 |
+
"loss": 0.5667279720306396,
|
| 312 |
+
"mean_token_accuracy": 0.8389136254787445,
|
| 313 |
+
"num_tokens": 705680.0,
|
| 314 |
+
"step": 300
|
| 315 |
+
},
|
| 316 |
+
{
|
| 317 |
+
"epoch": 0.7471980074719801,
|
| 318 |
+
"eval_entropy": 0.6141417321077612,
|
| 319 |
+
"eval_loss": 0.5570600628852844,
|
| 320 |
+
"eval_mean_token_accuracy": 0.8437647996253745,
|
| 321 |
+
"eval_num_tokens": 705680.0,
|
| 322 |
+
"eval_runtime": 86.7588,
|
| 323 |
+
"eval_samples_per_second": 15.86,
|
| 324 |
+
"eval_steps_per_second": 1.983,
|
| 325 |
+
"step": 300
|
| 326 |
+
},
|
| 327 |
+
{
|
| 328 |
+
"entropy": 0.6199494235217571,
|
| 329 |
+
"epoch": 0.797011207970112,
|
| 330 |
+
"grad_norm": 0.7924400568008423,
|
| 331 |
+
"learning_rate": 0.00015993892657950015,
|
| 332 |
+
"loss": 0.5529299736022949,
|
| 333 |
+
"mean_token_accuracy": 0.8426973208785057,
|
| 334 |
+
"num_tokens": 752616.0,
|
| 335 |
+
"step": 320
|
| 336 |
+
},
|
| 337 |
+
{
|
| 338 |
+
"epoch": 0.797011207970112,
|
| 339 |
+
"eval_entropy": 0.6133768925833147,
|
| 340 |
+
"eval_loss": 0.556602418422699,
|
| 341 |
+
"eval_mean_token_accuracy": 0.8432947965555413,
|
| 342 |
+
"eval_num_tokens": 752616.0,
|
| 343 |
+
"eval_runtime": 86.492,
|
| 344 |
+
"eval_samples_per_second": 15.909,
|
| 345 |
+
"eval_steps_per_second": 1.989,
|
| 346 |
+
"step": 320
|
| 347 |
+
},
|
| 348 |
+
{
|
| 349 |
+
"entropy": 0.6203986253589392,
|
| 350 |
+
"epoch": 0.8468244084682441,
|
| 351 |
+
"grad_norm": 0.8364354372024536,
|
| 352 |
+
"learning_rate": 0.00016996644548730578,
|
| 353 |
+
"loss": 0.5551144123077393,
|
| 354 |
+
"mean_token_accuracy": 0.8432973213493824,
|
| 355 |
+
"num_tokens": 797151.0,
|
| 356 |
+
"step": 340
|
| 357 |
+
},
|
| 358 |
+
{
|
| 359 |
+
"epoch": 0.8468244084682441,
|
| 360 |
+
"eval_entropy": 0.6017442844634833,
|
| 361 |
+
"eval_loss": 0.5566568374633789,
|
| 362 |
+
"eval_mean_token_accuracy": 0.8437666123689607,
|
| 363 |
+
"eval_num_tokens": 797151.0,
|
| 364 |
+
"eval_runtime": 86.5552,
|
| 365 |
+
"eval_samples_per_second": 15.897,
|
| 366 |
+
"eval_steps_per_second": 1.987,
|
| 367 |
+
"step": 340
|
| 368 |
+
},
|
| 369 |
+
{
|
| 370 |
+
"entropy": 0.6341533534228802,
|
| 371 |
+
"epoch": 0.8966376089663761,
|
| 372 |
+
"grad_norm": 0.7783445715904236,
|
| 373 |
+
"learning_rate": 0.00017999396439511144,
|
| 374 |
+
"loss": 0.5669133186340332,
|
| 375 |
+
"mean_token_accuracy": 0.8379446342587471,
|
| 376 |
+
"num_tokens": 843585.0,
|
| 377 |
+
"step": 360
|
| 378 |
+
},
|
| 379 |
+
{
|
| 380 |
+
"epoch": 0.8966376089663761,
|
| 381 |
+
"eval_entropy": 0.6055107958788095,
|
| 382 |
+
"eval_loss": 0.5599350333213806,
|
| 383 |
+
"eval_mean_token_accuracy": 0.8435030894917112,
|
| 384 |
+
"eval_num_tokens": 843585.0,
|
| 385 |
+
"eval_runtime": 86.4814,
|
| 386 |
+
"eval_samples_per_second": 15.911,
|
| 387 |
+
"eval_steps_per_second": 1.989,
|
| 388 |
+
"step": 360
|
| 389 |
+
},
|
| 390 |
+
{
|
| 391 |
+
"entropy": 0.6306198488920927,
|
| 392 |
+
"epoch": 0.9464508094645081,
|
| 393 |
+
"grad_norm": 0.8449786901473999,
|
| 394 |
+
"learning_rate": 0.0001900214833029171,
|
| 395 |
+
"loss": 0.5739435195922852,
|
| 396 |
+
"mean_token_accuracy": 0.8393832489848136,
|
| 397 |
+
"num_tokens": 889842.0,
|
| 398 |
+
"step": 380
|
| 399 |
+
},
|
| 400 |
+
{
|
| 401 |
+
"epoch": 0.9464508094645081,
|
| 402 |
+
"eval_entropy": 0.6129532439071078,
|
| 403 |
+
"eval_loss": 0.5566295981407166,
|
| 404 |
+
"eval_mean_token_accuracy": 0.8430350880290187,
|
| 405 |
+
"eval_num_tokens": 889842.0,
|
| 406 |
+
"eval_runtime": 86.4643,
|
| 407 |
+
"eval_samples_per_second": 15.914,
|
| 408 |
+
"eval_steps_per_second": 1.989,
|
| 409 |
+
"step": 380
|
| 410 |
+
},
|
| 411 |
+
{
|
| 412 |
+
"entropy": 0.6203123550862074,
|
| 413 |
+
"epoch": 0.9962640099626401,
|
| 414 |
+
"grad_norm": 0.7334314584732056,
|
| 415 |
+
"learning_rate": 0.00020004900221072276,
|
| 416 |
+
"loss": 0.5547565937042236,
|
| 417 |
+
"mean_token_accuracy": 0.8403573960065842,
|
| 418 |
+
"num_tokens": 935589.0,
|
| 419 |
+
"step": 400
|
| 420 |
+
},
|
| 421 |
+
{
|
| 422 |
+
"epoch": 0.9962640099626401,
|
| 423 |
+
"eval_entropy": 0.6275761647279873,
|
| 424 |
+
"eval_loss": 0.5621116757392883,
|
| 425 |
+
"eval_mean_token_accuracy": 0.841587379228237,
|
| 426 |
+
"eval_num_tokens": 935589.0,
|
| 427 |
+
"eval_runtime": 86.4748,
|
| 428 |
+
"eval_samples_per_second": 15.912,
|
| 429 |
+
"eval_steps_per_second": 1.989,
|
| 430 |
+
"step": 400
|
| 431 |
+
},
|
| 432 |
+
{
|
| 433 |
+
"entropy": 0.5795013002860241,
|
| 434 |
+
"epoch": 1.0448318804483188,
|
| 435 |
+
"grad_norm": 0.8858296871185303,
|
| 436 |
+
"learning_rate": 0.0002015421505577756,
|
| 437 |
+
"loss": 0.5183939933776855,
|
| 438 |
+
"mean_token_accuracy": 0.850081592034071,
|
| 439 |
+
"num_tokens": 980589.0,
|
| 440 |
+
"step": 420
|
| 441 |
+
},
|
| 442 |
+
{
|
| 443 |
+
"epoch": 1.0448318804483188,
|
| 444 |
+
"eval_entropy": 0.5583065545489622,
|
| 445 |
+
"eval_loss": 0.5605642199516296,
|
| 446 |
+
"eval_mean_token_accuracy": 0.8439708411000496,
|
| 447 |
+
"eval_num_tokens": 980589.0,
|
| 448 |
+
"eval_runtime": 86.5422,
|
| 449 |
+
"eval_samples_per_second": 15.9,
|
| 450 |
+
"eval_steps_per_second": 1.987,
|
| 451 |
+
"step": 420
|
| 452 |
+
},
|
| 453 |
+
{
|
| 454 |
+
"entropy": 0.5671238023787737,
|
| 455 |
+
"epoch": 1.0946450809464507,
|
| 456 |
+
"grad_norm": 0.6882498264312744,
|
| 457 |
+
"learning_rate": 0.00020150112347025443,
|
| 458 |
+
"loss": 0.5077326774597168,
|
| 459 |
+
"mean_token_accuracy": 0.8489868573844432,
|
| 460 |
+
"num_tokens": 1027852.0,
|
| 461 |
+
"step": 440
|
| 462 |
+
},
|
| 463 |
+
{
|
| 464 |
+
"epoch": 1.0946450809464507,
|
| 465 |
+
"eval_entropy": 0.5868900277933409,
|
| 466 |
+
"eval_loss": 0.5602695345878601,
|
| 467 |
+
"eval_mean_token_accuracy": 0.8428842161977014,
|
| 468 |
+
"eval_num_tokens": 1027852.0,
|
| 469 |
+
"eval_runtime": 86.623,
|
| 470 |
+
"eval_samples_per_second": 15.885,
|
| 471 |
+
"eval_steps_per_second": 1.986,
|
| 472 |
+
"step": 440
|
| 473 |
+
},
|
| 474 |
+
{
|
| 475 |
+
"entropy": 0.5533561781048775,
|
| 476 |
+
"epoch": 1.1444582814445827,
|
| 477 |
+
"grad_norm": 0.7717723250389099,
|
| 478 |
+
"learning_rate": 0.0002014297192297181,
|
| 479 |
+
"loss": 0.4954517364501953,
|
| 480 |
+
"mean_token_accuracy": 0.8529035650193691,
|
| 481 |
+
"num_tokens": 1077649.0,
|
| 482 |
+
"step": 460
|
| 483 |
+
},
|
| 484 |
+
{
|
| 485 |
+
"epoch": 1.1444582814445827,
|
| 486 |
+
"eval_entropy": 0.5600803743961246,
|
| 487 |
+
"eval_loss": 0.5608077645301819,
|
| 488 |
+
"eval_mean_token_accuracy": 0.8445036771685578,
|
| 489 |
+
"eval_num_tokens": 1077649.0,
|
| 490 |
+
"eval_runtime": 86.1316,
|
| 491 |
+
"eval_samples_per_second": 15.976,
|
| 492 |
+
"eval_steps_per_second": 1.997,
|
| 493 |
+
"step": 460
|
| 494 |
+
},
|
| 495 |
+
{
|
| 496 |
+
"entropy": 0.5692154694348573,
|
| 497 |
+
"epoch": 1.1942714819427147,
|
| 498 |
+
"grad_norm": 0.7322827577590942,
|
| 499 |
+
"learning_rate": 0.0002013279593707117,
|
| 500 |
+
"loss": 0.505049467086792,
|
| 501 |
+
"mean_token_accuracy": 0.8551576808094978,
|
| 502 |
+
"num_tokens": 1124872.0,
|
| 503 |
+
"step": 480
|
| 504 |
+
},
|
| 505 |
+
{
|
| 506 |
+
"epoch": 1.1942714819427147,
|
| 507 |
+
"eval_entropy": 0.5732695829383162,
|
| 508 |
+
"eval_loss": 0.5594323873519897,
|
| 509 |
+
"eval_mean_token_accuracy": 0.8449713407560836,
|
| 510 |
+
"eval_num_tokens": 1124872.0,
|
| 511 |
+
"eval_runtime": 86.2726,
|
| 512 |
+
"eval_samples_per_second": 15.949,
|
| 513 |
+
"eval_steps_per_second": 1.994,
|
| 514 |
+
"step": 480
|
| 515 |
+
},
|
| 516 |
+
{
|
| 517 |
+
"entropy": 0.5817618492990733,
|
| 518 |
+
"epoch": 1.244084682440847,
|
| 519 |
+
"grad_norm": 1.1776764392852783,
|
| 520 |
+
"learning_rate": 0.0002011958745826208,
|
| 521 |
+
"loss": 0.5137609958648681,
|
| 522 |
+
"mean_token_accuracy": 0.8521522544324398,
|
| 523 |
+
"num_tokens": 1168698.0,
|
| 524 |
+
"step": 500
|
| 525 |
+
},
|
| 526 |
+
{
|
| 527 |
+
"epoch": 1.244084682440847,
|
| 528 |
+
"eval_entropy": 0.5662581343636957,
|
| 529 |
+
"eval_loss": 0.5595026016235352,
|
| 530 |
+
"eval_mean_token_accuracy": 0.8441977164773053,
|
| 531 |
+
"eval_num_tokens": 1168698.0,
|
| 532 |
+
"eval_runtime": 86.7261,
|
| 533 |
+
"eval_samples_per_second": 15.866,
|
| 534 |
+
"eval_steps_per_second": 1.983,
|
| 535 |
+
"step": 500
|
| 536 |
+
},
|
| 537 |
+
{
|
| 538 |
+
"entropy": 0.5712925456464291,
|
| 539 |
+
"epoch": 1.293897882938979,
|
| 540 |
+
"grad_norm": 0.7960361838340759,
|
| 541 |
+
"learning_rate": 0.0002010335047004159,
|
| 542 |
+
"loss": 0.5134767532348633,
|
| 543 |
+
"mean_token_accuracy": 0.8513577707111836,
|
| 544 |
+
"num_tokens": 1216679.0,
|
| 545 |
+
"step": 520
|
| 546 |
+
},
|
| 547 |
+
{
|
| 548 |
+
"epoch": 1.293897882938979,
|
| 549 |
+
"eval_entropy": 0.5441222797299541,
|
| 550 |
+
"eval_loss": 0.5535460114479065,
|
| 551 |
+
"eval_mean_token_accuracy": 0.8450886118550633,
|
| 552 |
+
"eval_num_tokens": 1216679.0,
|
| 553 |
+
"eval_runtime": 86.2675,
|
| 554 |
+
"eval_samples_per_second": 15.95,
|
| 555 |
+
"eval_steps_per_second": 1.994,
|
| 556 |
+
"step": 520
|
| 557 |
+
},
|
| 558 |
+
{
|
| 559 |
+
"entropy": 0.5787045754492283,
|
| 560 |
+
"epoch": 1.3437110834371109,
|
| 561 |
+
"grad_norm": 0.9205410480499268,
|
| 562 |
+
"learning_rate": 0.00020084089869263887,
|
| 563 |
+
"loss": 0.5119701862335205,
|
| 564 |
+
"mean_token_accuracy": 0.8503516331315041,
|
| 565 |
+
"num_tokens": 1261365.0,
|
| 566 |
+
"step": 540
|
| 567 |
+
},
|
| 568 |
+
{
|
| 569 |
+
"epoch": 1.3437110834371109,
|
| 570 |
+
"eval_entropy": 0.5744457827057949,
|
| 571 |
+
"eval_loss": 0.5514978766441345,
|
| 572 |
+
"eval_mean_token_accuracy": 0.845929987901865,
|
| 573 |
+
"eval_num_tokens": 1261365.0,
|
| 574 |
+
"eval_runtime": 86.2299,
|
| 575 |
+
"eval_samples_per_second": 15.957,
|
| 576 |
+
"eval_steps_per_second": 1.995,
|
| 577 |
+
"step": 540
|
| 578 |
+
},
|
| 579 |
+
{
|
| 580 |
+
"entropy": 0.5739392962306737,
|
| 581 |
+
"epoch": 1.3935242839352429,
|
| 582 |
+
"grad_norm": 0.7475653886795044,
|
| 583 |
+
"learning_rate": 0.00020061811464663464,
|
| 584 |
+
"loss": 0.5189042091369629,
|
| 585 |
+
"mean_token_accuracy": 0.8492388024926185,
|
| 586 |
+
"num_tokens": 1306879.0,
|
| 587 |
+
"step": 560
|
| 588 |
+
},
|
| 589 |
+
{
|
| 590 |
+
"epoch": 1.3935242839352429,
|
| 591 |
+
"eval_entropy": 0.6116398271433142,
|
| 592 |
+
"eval_loss": 0.551732063293457,
|
| 593 |
+
"eval_mean_token_accuracy": 0.8450756967067719,
|
| 594 |
+
"eval_num_tokens": 1306879.0,
|
| 595 |
+
"eval_runtime": 86.6081,
|
| 596 |
+
"eval_samples_per_second": 15.888,
|
| 597 |
+
"eval_steps_per_second": 1.986,
|
| 598 |
+
"step": 560
|
| 599 |
+
},
|
| 600 |
+
{
|
| 601 |
+
"entropy": 0.5755622573196888,
|
| 602 |
+
"epoch": 1.4433374844333748,
|
| 603 |
+
"grad_norm": 0.8218411803245544,
|
| 604 |
+
"learning_rate": 0.00020036521975103286,
|
| 605 |
+
"loss": 0.5106248378753662,
|
| 606 |
+
"mean_token_accuracy": 0.8506785586476326,
|
| 607 |
+
"num_tokens": 1353534.0,
|
| 608 |
+
"step": 580
|
| 609 |
+
},
|
| 610 |
+
{
|
| 611 |
+
"epoch": 1.4433374844333748,
|
| 612 |
+
"eval_entropy": 0.5906928708386976,
|
| 613 |
+
"eval_loss": 0.551278829574585,
|
| 614 |
+
"eval_mean_token_accuracy": 0.8462819308042526,
|
| 615 |
+
"eval_num_tokens": 1353534.0,
|
| 616 |
+
"eval_runtime": 86.5438,
|
| 617 |
+
"eval_samples_per_second": 15.899,
|
| 618 |
+
"eval_steps_per_second": 1.987,
|
| 619 |
+
"step": 580
|
| 620 |
+
},
|
| 621 |
+
{
|
| 622 |
+
"entropy": 0.5694822132587433,
|
| 623 |
+
"epoch": 1.4931506849315068,
|
| 624 |
+
"grad_norm": 0.8880652189254761,
|
| 625 |
+
"learning_rate": 0.00020008229027548475,
|
| 626 |
+
"loss": 0.5140334606170655,
|
| 627 |
+
"mean_token_accuracy": 0.8521522797644139,
|
| 628 |
+
"num_tokens": 1399537.0,
|
| 629 |
+
"step": 600
|
| 630 |
+
},
|
| 631 |
+
{
|
| 632 |
+
"epoch": 1.4931506849315068,
|
| 633 |
+
"eval_entropy": 0.5599641964532608,
|
| 634 |
+
"eval_loss": 0.5501875877380371,
|
| 635 |
+
"eval_mean_token_accuracy": 0.8467660788879838,
|
| 636 |
+
"eval_num_tokens": 1399537.0,
|
| 637 |
+
"eval_runtime": 86.6458,
|
| 638 |
+
"eval_samples_per_second": 15.881,
|
| 639 |
+
"eval_steps_per_second": 1.985,
|
| 640 |
+
"step": 600
|
| 641 |
+
},
|
| 642 |
+
{
|
| 643 |
+
"entropy": 0.5675108034163714,
|
| 644 |
+
"epoch": 1.5429638854296388,
|
| 645 |
+
"grad_norm": 0.837087094783783,
|
| 646 |
+
"learning_rate": 0.0001997694115476612,
|
| 647 |
+
"loss": 0.5099846363067627,
|
| 648 |
+
"mean_token_accuracy": 0.8543680295348167,
|
| 649 |
+
"num_tokens": 1448422.0,
|
| 650 |
+
"step": 620
|
| 651 |
+
},
|
| 652 |
+
{
|
| 653 |
+
"epoch": 1.5429638854296388,
|
| 654 |
+
"eval_entropy": 0.5728072581249614,
|
| 655 |
+
"eval_loss": 0.5445425510406494,
|
| 656 |
+
"eval_mean_token_accuracy": 0.8474342175001321,
|
| 657 |
+
"eval_num_tokens": 1448422.0,
|
| 658 |
+
"eval_runtime": 86.4859,
|
| 659 |
+
"eval_samples_per_second": 15.91,
|
| 660 |
+
"eval_steps_per_second": 1.989,
|
| 661 |
+
"step": 620
|
| 662 |
+
},
|
| 663 |
+
{
|
| 664 |
+
"entropy": 0.5700885068625212,
|
| 665 |
+
"epoch": 1.592777085927771,
|
| 666 |
+
"grad_norm": 0.6598765850067139,
|
| 667 |
+
"learning_rate": 0.000199426677927519,
|
| 668 |
+
"loss": 0.5122694969177246,
|
| 669 |
+
"mean_token_accuracy": 0.8519927568733692,
|
| 670 |
+
"num_tokens": 1495009.0,
|
| 671 |
+
"step": 640
|
| 672 |
+
},
|
| 673 |
+
{
|
| 674 |
+
"epoch": 1.592777085927771,
|
| 675 |
+
"eval_entropy": 0.5476993622128353,
|
| 676 |
+
"eval_loss": 0.5427973866462708,
|
| 677 |
+
"eval_mean_token_accuracy": 0.8478512147138285,
|
| 678 |
+
"eval_num_tokens": 1495009.0,
|
| 679 |
+
"eval_runtime": 86.4172,
|
| 680 |
+
"eval_samples_per_second": 15.923,
|
| 681 |
+
"eval_steps_per_second": 1.99,
|
| 682 |
+
"step": 640
|
| 683 |
+
},
|
| 684 |
+
{
|
| 685 |
+
"entropy": 0.5829229176044464,
|
| 686 |
+
"epoch": 1.6425902864259028,
|
| 687 |
+
"grad_norm": 0.6965194940567017,
|
| 688 |
+
"learning_rate": 0.00019905419277884342,
|
| 689 |
+
"loss": 0.5253659725189209,
|
| 690 |
+
"mean_token_accuracy": 0.8493309423327446,
|
| 691 |
+
"num_tokens": 1536932.0,
|
| 692 |
+
"step": 660
|
| 693 |
+
},
|
| 694 |
+
{
|
| 695 |
+
"epoch": 1.6425902864259028,
|
| 696 |
+
"eval_entropy": 0.5666290084983028,
|
| 697 |
+
"eval_loss": 0.5467478036880493,
|
| 698 |
+
"eval_mean_token_accuracy": 0.8479407703460649,
|
| 699 |
+
"eval_num_tokens": 1536932.0,
|
| 700 |
+
"eval_runtime": 86.4414,
|
| 701 |
+
"eval_samples_per_second": 15.918,
|
| 702 |
+
"eval_steps_per_second": 1.99,
|
| 703 |
+
"step": 660
|
| 704 |
+
},
|
| 705 |
+
{
|
| 706 |
+
"entropy": 0.5498311135917902,
|
| 707 |
+
"epoch": 1.692403486924035,
|
| 708 |
+
"grad_norm": 0.636583685874939,
|
| 709 |
+
"learning_rate": 0.00019865206843807482,
|
| 710 |
+
"loss": 0.49981012344360354,
|
| 711 |
+
"mean_token_accuracy": 0.8560848504304885,
|
| 712 |
+
"num_tokens": 1585718.0,
|
| 713 |
+
"step": 680
|
| 714 |
+
},
|
| 715 |
+
{
|
| 716 |
+
"epoch": 1.692403486924035,
|
| 717 |
+
"eval_entropy": 0.539117265406043,
|
| 718 |
+
"eval_loss": 0.53994220495224,
|
| 719 |
+
"eval_mean_token_accuracy": 0.8488582601380903,
|
| 720 |
+
"eval_num_tokens": 1585718.0,
|
| 721 |
+
"eval_runtime": 86.5296,
|
| 722 |
+
"eval_samples_per_second": 15.902,
|
| 723 |
+
"eval_steps_per_second": 1.988,
|
| 724 |
+
"step": 680
|
| 725 |
+
},
|
| 726 |
+
{
|
| 727 |
+
"entropy": 0.5543891470879316,
|
| 728 |
+
"epoch": 1.7422166874221667,
|
| 729 |
+
"grad_norm": 0.6068442463874817,
|
| 730 |
+
"learning_rate": 0.0001982204261804297,
|
| 731 |
+
"loss": 0.498047399520874,
|
| 732 |
+
"mean_token_accuracy": 0.8554679051041603,
|
| 733 |
+
"num_tokens": 1635718.0,
|
| 734 |
+
"step": 700
|
| 735 |
+
},
|
| 736 |
+
{
|
| 737 |
+
"epoch": 1.7422166874221667,
|
| 738 |
+
"eval_entropy": 0.5703774151760478,
|
| 739 |
+
"eval_loss": 0.5300245881080627,
|
| 740 |
+
"eval_mean_token_accuracy": 0.850798153946566,
|
| 741 |
+
"eval_num_tokens": 1635718.0,
|
| 742 |
+
"eval_runtime": 86.6456,
|
| 743 |
+
"eval_samples_per_second": 15.881,
|
| 744 |
+
"eval_steps_per_second": 1.985,
|
| 745 |
+
"step": 700
|
| 746 |
+
},
|
| 747 |
+
{
|
| 748 |
+
"entropy": 0.546524541825056,
|
| 749 |
+
"epoch": 1.792029887920299,
|
| 750 |
+
"grad_norm": 0.7274155020713806,
|
| 751 |
+
"learning_rate": 0.00019775939618332566,
|
| 752 |
+
"loss": 0.4988589286804199,
|
| 753 |
+
"mean_token_accuracy": 0.853422473371029,
|
| 754 |
+
"num_tokens": 1681291.0,
|
| 755 |
+
"step": 720
|
| 756 |
+
},
|
| 757 |
+
{
|
| 758 |
+
"epoch": 1.792029887920299,
|
| 759 |
+
"eval_entropy": 0.5614905688305234,
|
| 760 |
+
"eval_loss": 0.5350332260131836,
|
| 761 |
+
"eval_mean_token_accuracy": 0.8492204359797544,
|
| 762 |
+
"eval_num_tokens": 1681291.0,
|
| 763 |
+
"eval_runtime": 86.7581,
|
| 764 |
+
"eval_samples_per_second": 15.86,
|
| 765 |
+
"eval_steps_per_second": 1.983,
|
| 766 |
+
"step": 720
|
| 767 |
+
},
|
| 768 |
+
{
|
| 769 |
+
"entropy": 0.5519792139530182,
|
| 770 |
+
"epoch": 1.841843088418431,
|
| 771 |
+
"grad_norm": 0.663466215133667,
|
| 772 |
+
"learning_rate": 0.00019726911748712167,
|
| 773 |
+
"loss": 0.5099314212799072,
|
| 774 |
+
"mean_token_accuracy": 0.848412600159645,
|
| 775 |
+
"num_tokens": 1729102.0,
|
| 776 |
+
"step": 740
|
| 777 |
+
},
|
| 778 |
+
{
|
| 779 |
+
"epoch": 1.841843088418431,
|
| 780 |
+
"eval_entropy": 0.5583519090053647,
|
| 781 |
+
"eval_loss": 0.530483603477478,
|
| 782 |
+
"eval_mean_token_accuracy": 0.8500003374593202,
|
| 783 |
+
"eval_num_tokens": 1729102.0,
|
| 784 |
+
"eval_runtime": 86.3961,
|
| 785 |
+
"eval_samples_per_second": 15.927,
|
| 786 |
+
"eval_steps_per_second": 1.991,
|
| 787 |
+
"step": 740
|
| 788 |
+
},
|
| 789 |
+
{
|
| 790 |
+
"entropy": 0.5454779766499996,
|
| 791 |
+
"epoch": 1.891656288916563,
|
| 792 |
+
"grad_norm": 0.890394926071167,
|
| 793 |
+
"learning_rate": 0.00019674973795318548,
|
| 794 |
+
"loss": 0.4931994915008545,
|
| 795 |
+
"mean_token_accuracy": 0.8540832489728928,
|
| 796 |
+
"num_tokens": 1773578.0,
|
| 797 |
+
"step": 760
|
| 798 |
+
},
|
| 799 |
+
{
|
| 800 |
+
"epoch": 1.891656288916563,
|
| 801 |
+
"eval_entropy": 0.572755502406941,
|
| 802 |
+
"eval_loss": 0.5415747761726379,
|
| 803 |
+
"eval_mean_token_accuracy": 0.8444425803284312,
|
| 804 |
+
"eval_num_tokens": 1773578.0,
|
| 805 |
+
"eval_runtime": 86.4323,
|
| 806 |
+
"eval_samples_per_second": 15.92,
|
| 807 |
+
"eval_steps_per_second": 1.99,
|
| 808 |
+
"step": 760
|
| 809 |
+
},
|
| 810 |
+
{
|
| 811 |
+
"entropy": 0.5392089951783419,
|
| 812 |
+
"epoch": 1.9414694894146949,
|
| 813 |
+
"grad_norm": 0.632411777973175,
|
| 814 |
+
"learning_rate": 0.00019620141421930058,
|
| 815 |
+
"loss": 0.4957888603210449,
|
| 816 |
+
"mean_token_accuracy": 0.8549866065382957,
|
| 817 |
+
"num_tokens": 1821725.0,
|
| 818 |
+
"step": 780
|
| 819 |
+
},
|
| 820 |
+
{
|
| 821 |
+
"epoch": 1.9414694894146949,
|
| 822 |
+
"eval_entropy": 0.540764772961306,
|
| 823 |
+
"eval_loss": 0.5327216386795044,
|
| 824 |
+
"eval_mean_token_accuracy": 0.850631088364956,
|
| 825 |
+
"eval_num_tokens": 1821725.0,
|
| 826 |
+
"eval_runtime": 86.8097,
|
| 827 |
+
"eval_samples_per_second": 15.851,
|
| 828 |
+
"eval_steps_per_second": 1.981,
|
| 829 |
+
"step": 780
|
| 830 |
+
},
|
| 831 |
+
{
|
| 832 |
+
"entropy": 0.5674678739160299,
|
| 833 |
+
"epoch": 1.9912826899128269,
|
| 834 |
+
"grad_norm": 0.6958843469619751,
|
| 835 |
+
"learning_rate": 0.0001956243116524263,
|
| 836 |
+
"loss": 0.504389762878418,
|
| 837 |
+
"mean_token_accuracy": 0.8527948908507824,
|
| 838 |
+
"num_tokens": 1868431.0,
|
| 839 |
+
"step": 800
|
| 840 |
+
},
|
| 841 |
+
{
|
| 842 |
+
"epoch": 1.9912826899128269,
|
| 843 |
+
"eval_entropy": 0.530262403190136,
|
| 844 |
+
"eval_loss": 0.5308871865272522,
|
| 845 |
+
"eval_mean_token_accuracy": 0.8522498046242913,
|
| 846 |
+
"eval_num_tokens": 1868431.0,
|
| 847 |
+
"eval_runtime": 86.7942,
|
| 848 |
+
"eval_samples_per_second": 15.854,
|
| 849 |
+
"eval_steps_per_second": 1.982,
|
| 850 |
+
"step": 800
|
| 851 |
+
},
|
| 852 |
+
{
|
| 853 |
+
"entropy": 0.4742849511213792,
|
| 854 |
+
"epoch": 2.0398505603985058,
|
| 855 |
+
"grad_norm": 0.6941492557525635,
|
| 856 |
+
"learning_rate": 0.00019501860429882556,
|
| 857 |
+
"loss": 0.418599271774292,
|
| 858 |
+
"mean_token_accuracy": 0.8748210859604371,
|
| 859 |
+
"num_tokens": 1915280.0,
|
| 860 |
+
"step": 820
|
| 861 |
+
},
|
| 862 |
+
{
|
| 863 |
+
"epoch": 2.0398505603985058,
|
| 864 |
+
"eval_entropy": 0.504602165069691,
|
| 865 |
+
"eval_loss": 0.542878270149231,
|
| 866 |
+
"eval_mean_token_accuracy": 0.8507604484641275,
|
| 867 |
+
"eval_num_tokens": 1915280.0,
|
| 868 |
+
"eval_runtime": 86.7841,
|
| 869 |
+
"eval_samples_per_second": 15.855,
|
| 870 |
+
"eval_steps_per_second": 1.982,
|
| 871 |
+
"step": 820
|
| 872 |
+
},
|
| 873 |
+
{
|
| 874 |
+
"entropy": 0.45857742577791216,
|
| 875 |
+
"epoch": 2.0896637608966375,
|
| 876 |
+
"grad_norm": 0.5791997909545898,
|
| 877 |
+
"learning_rate": 0.00019438447483157478,
|
| 878 |
+
"loss": 0.399777889251709,
|
| 879 |
+
"mean_token_accuracy": 0.8754058346152306,
|
| 880 |
+
"num_tokens": 1965306.0,
|
| 881 |
+
"step": 840
|
| 882 |
+
},
|
| 883 |
+
{
|
| 884 |
+
"epoch": 2.0896637608966375,
|
| 885 |
+
"eval_entropy": 0.5028848362176918,
|
| 886 |
+
"eval_loss": 0.5356478095054626,
|
| 887 |
+
"eval_mean_token_accuracy": 0.8525635412959165,
|
| 888 |
+
"eval_num_tokens": 1965306.0,
|
| 889 |
+
"eval_runtime": 86.6707,
|
| 890 |
+
"eval_samples_per_second": 15.876,
|
| 891 |
+
"eval_steps_per_second": 1.985,
|
| 892 |
+
"step": 840
|
| 893 |
+
},
|
| 894 |
+
{
|
| 895 |
+
"entropy": 0.4869446292519569,
|
| 896 |
+
"epoch": 2.1394769613947697,
|
| 897 |
+
"grad_norm": 0.6483516693115234,
|
| 898 |
+
"learning_rate": 0.00019372211449547223,
|
| 899 |
+
"loss": 0.40715818405151366,
|
| 900 |
+
"mean_token_accuracy": 0.875113020837307,
|
| 901 |
+
"num_tokens": 2008562.0,
|
| 902 |
+
"step": 860
|
| 903 |
+
},
|
| 904 |
+
{
|
| 905 |
+
"epoch": 2.1394769613947697,
|
| 906 |
+
"eval_entropy": 0.4928991326759028,
|
| 907 |
+
"eval_loss": 0.5419561862945557,
|
| 908 |
+
"eval_mean_token_accuracy": 0.8516040146350861,
|
| 909 |
+
"eval_num_tokens": 2008562.0,
|
| 910 |
+
"eval_runtime": 87.0686,
|
| 911 |
+
"eval_samples_per_second": 15.804,
|
| 912 |
+
"eval_steps_per_second": 1.975,
|
| 913 |
+
"step": 860
|
| 914 |
+
},
|
| 915 |
+
{
|
| 916 |
+
"entropy": 0.45819590501487256,
|
| 917 |
+
"epoch": 2.1892901618929015,
|
| 918 |
+
"grad_norm": 0.6661920547485352,
|
| 919 |
+
"learning_rate": 0.00019303172304936108,
|
| 920 |
+
"loss": 0.39511430263519287,
|
| 921 |
+
"mean_token_accuracy": 0.8780680045485496,
|
| 922 |
+
"num_tokens": 2056474.0,
|
| 923 |
+
"step": 880
|
| 924 |
+
},
|
| 925 |
+
{
|
| 926 |
+
"epoch": 2.1892901618929015,
|
| 927 |
+
"eval_entropy": 0.48602560647698334,
|
| 928 |
+
"eval_loss": 0.5436084866523743,
|
| 929 |
+
"eval_mean_token_accuracy": 0.8500938470973525,
|
| 930 |
+
"eval_num_tokens": 2056474.0,
|
| 931 |
+
"eval_runtime": 86.6809,
|
| 932 |
+
"eval_samples_per_second": 15.874,
|
| 933 |
+
"eval_steps_per_second": 1.984,
|
| 934 |
+
"step": 880
|
| 935 |
+
},
|
| 936 |
+
{
|
| 937 |
+
"entropy": 0.4780638810247183,
|
| 938 |
+
"epoch": 2.2391033623910337,
|
| 939 |
+
"grad_norm": 0.6870484352111816,
|
| 940 |
+
"learning_rate": 0.0001923135087058851,
|
| 941 |
+
"loss": 0.4061615467071533,
|
| 942 |
+
"mean_token_accuracy": 0.8766494184732437,
|
| 943 |
+
"num_tokens": 2103543.0,
|
| 944 |
+
"step": 900
|
| 945 |
+
},
|
| 946 |
+
{
|
| 947 |
+
"epoch": 2.2391033623910337,
|
| 948 |
+
"eval_entropy": 0.48236206035281337,
|
| 949 |
+
"eval_loss": 0.5446090698242188,
|
| 950 |
+
"eval_mean_token_accuracy": 0.8507725513258646,
|
| 951 |
+
"eval_num_tokens": 2103543.0,
|
| 952 |
+
"eval_runtime": 86.7398,
|
| 953 |
+
"eval_samples_per_second": 15.864,
|
| 954 |
+
"eval_steps_per_second": 1.983,
|
| 955 |
+
"step": 900
|
| 956 |
+
},
|
| 957 |
+
{
|
| 958 |
+
"entropy": 0.463029869645834,
|
| 959 |
+
"epoch": 2.2889165628891655,
|
| 960 |
+
"grad_norm": 0.6894590854644775,
|
| 961 |
+
"learning_rate": 0.00019156768806869427,
|
| 962 |
+
"loss": 0.39602413177490237,
|
| 963 |
+
"mean_token_accuracy": 0.876420046389103,
|
| 964 |
+
"num_tokens": 2147861.0,
|
| 965 |
+
"step": 920
|
| 966 |
+
},
|
| 967 |
+
{
|
| 968 |
+
"epoch": 2.2889165628891655,
|
| 969 |
+
"eval_entropy": 0.4904779093556626,
|
| 970 |
+
"eval_loss": 0.5404934287071228,
|
| 971 |
+
"eval_mean_token_accuracy": 0.852238280828609,
|
| 972 |
+
"eval_num_tokens": 2147861.0,
|
| 973 |
+
"eval_runtime": 86.5348,
|
| 974 |
+
"eval_samples_per_second": 15.901,
|
| 975 |
+
"eval_steps_per_second": 1.988,
|
| 976 |
+
"step": 920
|
| 977 |
+
},
|
| 978 |
+
{
|
| 979 |
+
"entropy": 0.4817025110125542,
|
| 980 |
+
"epoch": 2.3387297633872977,
|
| 981 |
+
"grad_norm": 0.7756227254867554,
|
| 982 |
+
"learning_rate": 0.00019079448606712033,
|
| 983 |
+
"loss": 0.4177968502044678,
|
| 984 |
+
"mean_token_accuracy": 0.8712256088852882,
|
| 985 |
+
"num_tokens": 2190561.0,
|
| 986 |
+
"step": 940
|
| 987 |
+
},
|
| 988 |
+
{
|
| 989 |
+
"epoch": 2.3387297633872977,
|
| 990 |
+
"eval_entropy": 0.5153802815218305,
|
| 991 |
+
"eval_loss": 0.5424937605857849,
|
| 992 |
+
"eval_mean_token_accuracy": 0.8506565759348315,
|
| 993 |
+
"eval_num_tokens": 2190561.0,
|
| 994 |
+
"eval_runtime": 86.8973,
|
| 995 |
+
"eval_samples_per_second": 15.835,
|
| 996 |
+
"eval_steps_per_second": 1.979,
|
| 997 |
+
"step": 940
|
| 998 |
+
},
|
| 999 |
+
{
|
| 1000 |
+
"entropy": 0.46456389091908934,
|
| 1001 |
+
"epoch": 2.3885429638854294,
|
| 1002 |
+
"grad_norm": 1.2000319957733154,
|
| 1003 |
+
"learning_rate": 0.00018999413588834105,
|
| 1004 |
+
"loss": 0.4084665775299072,
|
| 1005 |
+
"mean_token_accuracy": 0.8750658087432385,
|
| 1006 |
+
"num_tokens": 2239412.0,
|
| 1007 |
+
"step": 960
|
| 1008 |
+
},
|
| 1009 |
+
{
|
| 1010 |
+
"epoch": 2.3885429638854294,
|
| 1011 |
+
"eval_entropy": 0.4849439303195754,
|
| 1012 |
+
"eval_loss": 0.545662522315979,
|
| 1013 |
+
"eval_mean_token_accuracy": 0.8491013112456299,
|
| 1014 |
+
"eval_num_tokens": 2239412.0,
|
| 1015 |
+
"eval_runtime": 86.9049,
|
| 1016 |
+
"eval_samples_per_second": 15.833,
|
| 1017 |
+
"eval_steps_per_second": 1.979,
|
| 1018 |
+
"step": 960
|
| 1019 |
+
},
|
| 1020 |
+
{
|
| 1021 |
+
"entropy": 0.4857471022754908,
|
| 1022 |
+
"epoch": 2.4383561643835616,
|
| 1023 |
+
"grad_norm": 0.9696341753005981,
|
| 1024 |
+
"learning_rate": 0.0001891668789070541,
|
| 1025 |
+
"loss": 0.4149796962738037,
|
| 1026 |
+
"mean_token_accuracy": 0.8704176343977451,
|
| 1027 |
+
"num_tokens": 2286283.0,
|
| 1028 |
+
"step": 980
|
| 1029 |
+
},
|
| 1030 |
+
{
|
| 1031 |
+
"epoch": 2.4383561643835616,
|
| 1032 |
+
"eval_entropy": 0.4872790058684904,
|
| 1033 |
+
"eval_loss": 0.5412707924842834,
|
| 1034 |
+
"eval_mean_token_accuracy": 0.8509329602468846,
|
| 1035 |
+
"eval_num_tokens": 2286283.0,
|
| 1036 |
+
"eval_runtime": 86.7846,
|
| 1037 |
+
"eval_samples_per_second": 15.855,
|
| 1038 |
+
"eval_steps_per_second": 1.982,
|
| 1039 |
+
"step": 980
|
| 1040 |
+
},
|
| 1041 |
+
{
|
| 1042 |
+
"entropy": 0.4727417893707752,
|
| 1043 |
+
"epoch": 2.488169364881694,
|
| 1044 |
+
"grad_norm": 0.7852500677108765,
|
| 1045 |
+
"learning_rate": 0.0001883129646126818,
|
| 1046 |
+
"loss": 0.4142886161804199,
|
| 1047 |
+
"mean_token_accuracy": 0.8712429471313954,
|
| 1048 |
+
"num_tokens": 2333733.0,
|
| 1049 |
+
"step": 1000
|
| 1050 |
+
},
|
| 1051 |
+
{
|
| 1052 |
+
"epoch": 2.488169364881694,
|
| 1053 |
+
"eval_entropy": 0.5386548059624295,
|
| 1054 |
+
"eval_loss": 0.536101222038269,
|
| 1055 |
+
"eval_mean_token_accuracy": 0.8499491239009902,
|
| 1056 |
+
"eval_num_tokens": 2333733.0,
|
| 1057 |
+
"eval_runtime": 86.9501,
|
| 1058 |
+
"eval_samples_per_second": 15.825,
|
| 1059 |
+
"eval_steps_per_second": 1.978,
|
| 1060 |
+
"step": 1000
|
| 1061 |
+
},
|
| 1062 |
+
{
|
| 1063 |
+
"entropy": 0.4673406321555376,
|
| 1064 |
+
"epoch": 2.5379825653798256,
|
| 1065 |
+
"grad_norm": 0.7133921384811401,
|
| 1066 |
+
"learning_rate": 0.0001874326505341286,
|
| 1067 |
+
"loss": 0.40857529640197754,
|
| 1068 |
+
"mean_token_accuracy": 0.8747925907373428,
|
| 1069 |
+
"num_tokens": 2384270.0,
|
| 1070 |
+
"step": 1020
|
| 1071 |
+
},
|
| 1072 |
+
{
|
| 1073 |
+
"epoch": 2.5379825653798256,
|
| 1074 |
+
"eval_entropy": 0.495788364909416,
|
| 1075 |
+
"eval_loss": 0.5418923497200012,
|
| 1076 |
+
"eval_mean_token_accuracy": 0.851321972040243,
|
| 1077 |
+
"eval_num_tokens": 2384270.0,
|
| 1078 |
+
"eval_runtime": 86.7154,
|
| 1079 |
+
"eval_samples_per_second": 15.868,
|
| 1080 |
+
"eval_steps_per_second": 1.983,
|
| 1081 |
+
"step": 1020
|
| 1082 |
+
},
|
| 1083 |
+
{
|
| 1084 |
+
"entropy": 0.47599745728075504,
|
| 1085 |
+
"epoch": 2.587795765877958,
|
| 1086 |
+
"grad_norm": 0.8202953338623047,
|
| 1087 |
+
"learning_rate": 0.0001865262021621137,
|
| 1088 |
+
"loss": 0.40998234748840334,
|
| 1089 |
+
"mean_token_accuracy": 0.8758242674171924,
|
| 1090 |
+
"num_tokens": 2428036.0,
|
| 1091 |
+
"step": 1040
|
| 1092 |
+
},
|
| 1093 |
+
{
|
| 1094 |
+
"epoch": 2.587795765877958,
|
| 1095 |
+
"eval_entropy": 0.4887966953737791,
|
| 1096 |
+
"eval_loss": 0.5408804416656494,
|
| 1097 |
+
"eval_mean_token_accuracy": 0.8512661065473113,
|
| 1098 |
+
"eval_num_tokens": 2428036.0,
|
| 1099 |
+
"eval_runtime": 86.7869,
|
| 1100 |
+
"eval_samples_per_second": 15.855,
|
| 1101 |
+
"eval_steps_per_second": 1.982,
|
| 1102 |
+
"step": 1040
|
| 1103 |
+
},
|
| 1104 |
+
{
|
| 1105 |
+
"entropy": 0.4824396539479494,
|
| 1106 |
+
"epoch": 2.6376089663760895,
|
| 1107 |
+
"grad_norm": 0.6507360935211182,
|
| 1108 |
+
"learning_rate": 0.00018559389286910275,
|
| 1109 |
+
"loss": 0.4165764808654785,
|
| 1110 |
+
"mean_token_accuracy": 0.8722914069890976,
|
| 1111 |
+
"num_tokens": 2476815.0,
|
| 1112 |
+
"step": 1060
|
| 1113 |
+
},
|
| 1114 |
+
{
|
| 1115 |
+
"epoch": 2.6376089663760895,
|
| 1116 |
+
"eval_entropy": 0.4793398808254752,
|
| 1117 |
+
"eval_loss": 0.5326959490776062,
|
| 1118 |
+
"eval_mean_token_accuracy": 0.8534493650807891,
|
| 1119 |
+
"eval_num_tokens": 2476815.0,
|
| 1120 |
+
"eval_runtime": 86.9559,
|
| 1121 |
+
"eval_samples_per_second": 15.824,
|
| 1122 |
+
"eval_steps_per_second": 1.978,
|
| 1123 |
+
"step": 1060
|
| 1124 |
+
},
|
| 1125 |
+
{
|
| 1126 |
+
"entropy": 0.4605010639876127,
|
| 1127 |
+
"epoch": 2.6874221668742218,
|
| 1128 |
+
"grad_norm": 0.6740535497665405,
|
| 1129 |
+
"learning_rate": 0.00018463600382686253,
|
| 1130 |
+
"loss": 0.4123940944671631,
|
| 1131 |
+
"mean_token_accuracy": 0.8733638986945153,
|
| 1132 |
+
"num_tokens": 2527131.0,
|
| 1133 |
+
"step": 1080
|
| 1134 |
+
},
|
| 1135 |
+
{
|
| 1136 |
+
"epoch": 2.6874221668742218,
|
| 1137 |
+
"eval_entropy": 0.47902208583992584,
|
| 1138 |
+
"eval_loss": 0.5372340083122253,
|
| 1139 |
+
"eval_mean_token_accuracy": 0.851325950303743,
|
| 1140 |
+
"eval_num_tokens": 2527131.0,
|
| 1141 |
+
"eval_runtime": 86.9638,
|
| 1142 |
+
"eval_samples_per_second": 15.823,
|
| 1143 |
+
"eval_steps_per_second": 1.978,
|
| 1144 |
+
"step": 1080
|
| 1145 |
+
},
|
| 1146 |
+
{
|
| 1147 |
+
"entropy": 0.4872019402682781,
|
| 1148 |
+
"epoch": 2.7372353673723535,
|
| 1149 |
+
"grad_norm": 0.6994742155075073,
|
| 1150 |
+
"learning_rate": 0.0001836528239216632,
|
| 1151 |
+
"loss": 0.41599602699279786,
|
| 1152 |
+
"mean_token_accuracy": 0.872775862365961,
|
| 1153 |
+
"num_tokens": 2572537.0,
|
| 1154 |
+
"step": 1100
|
| 1155 |
+
},
|
| 1156 |
+
{
|
| 1157 |
+
"epoch": 2.7372353673723535,
|
| 1158 |
+
"eval_entropy": 0.4893243626453156,
|
| 1159 |
+
"eval_loss": 0.5327795743942261,
|
| 1160 |
+
"eval_mean_token_accuracy": 0.8537560302850812,
|
| 1161 |
+
"eval_num_tokens": 2572537.0,
|
| 1162 |
+
"eval_runtime": 86.823,
|
| 1163 |
+
"eval_samples_per_second": 15.848,
|
| 1164 |
+
"eval_steps_per_second": 1.981,
|
| 1165 |
+
"step": 1100
|
| 1166 |
+
},
|
| 1167 |
+
{
|
| 1168 |
+
"entropy": 0.4949610233306885,
|
| 1169 |
+
"epoch": 2.7870485678704857,
|
| 1170 |
+
"grad_norm": 0.9605912566184998,
|
| 1171 |
+
"learning_rate": 0.0001826446496671543,
|
| 1172 |
+
"loss": 0.4266993045806885,
|
| 1173 |
+
"mean_token_accuracy": 0.8688005246222019,
|
| 1174 |
+
"num_tokens": 2616047.0,
|
| 1175 |
+
"step": 1120
|
| 1176 |
+
},
|
| 1177 |
+
{
|
| 1178 |
+
"epoch": 2.7870485678704857,
|
| 1179 |
+
"eval_entropy": 0.5061517927882283,
|
| 1180 |
+
"eval_loss": 0.5356810092926025,
|
| 1181 |
+
"eval_mean_token_accuracy": 0.8524593568818514,
|
| 1182 |
+
"eval_num_tokens": 2616047.0,
|
| 1183 |
+
"eval_runtime": 86.8385,
|
| 1184 |
+
"eval_samples_per_second": 15.846,
|
| 1185 |
+
"eval_steps_per_second": 1.981,
|
| 1186 |
+
"step": 1120
|
| 1187 |
+
},
|
| 1188 |
+
{
|
| 1189 |
+
"entropy": 0.48401356525719164,
|
| 1190 |
+
"epoch": 2.8368617683686175,
|
| 1191 |
+
"grad_norm": 0.6332499980926514,
|
| 1192 |
+
"learning_rate": 0.00018161178511494022,
|
| 1193 |
+
"loss": 0.42131738662719725,
|
| 1194 |
+
"mean_token_accuracy": 0.8729447312653065,
|
| 1195 |
+
"num_tokens": 2664744.0,
|
| 1196 |
+
"step": 1140
|
| 1197 |
+
},
|
| 1198 |
+
{
|
| 1199 |
+
"epoch": 2.8368617683686175,
|
| 1200 |
+
"eval_entropy": 0.48792897060860035,
|
| 1201 |
+
"eval_loss": 0.5290402173995972,
|
| 1202 |
+
"eval_mean_token_accuracy": 0.853078076659247,
|
| 1203 |
+
"eval_num_tokens": 2664744.0,
|
| 1204 |
+
"eval_runtime": 86.7746,
|
| 1205 |
+
"eval_samples_per_second": 15.857,
|
| 1206 |
+
"eval_steps_per_second": 1.982,
|
| 1207 |
+
"step": 1140
|
| 1208 |
+
},
|
| 1209 |
+
{
|
| 1210 |
+
"entropy": 0.48017631396651267,
|
| 1211 |
+
"epoch": 2.8866749688667497,
|
| 1212 |
+
"grad_norm": 0.8013222217559814,
|
| 1213 |
+
"learning_rate": 0.00018055454176288234,
|
| 1214 |
+
"loss": 0.4195223808288574,
|
| 1215 |
+
"mean_token_accuracy": 0.8721428856253624,
|
| 1216 |
+
"num_tokens": 2710196.0,
|
| 1217 |
+
"step": 1160
|
| 1218 |
+
},
|
| 1219 |
+
{
|
| 1220 |
+
"epoch": 2.8866749688667497,
|
| 1221 |
+
"eval_entropy": 0.5205728571082271,
|
| 1222 |
+
"eval_loss": 0.5242091417312622,
|
| 1223 |
+
"eval_mean_token_accuracy": 0.8535184077052183,
|
| 1224 |
+
"eval_num_tokens": 2710196.0,
|
| 1225 |
+
"eval_runtime": 87.009,
|
| 1226 |
+
"eval_samples_per_second": 15.814,
|
| 1227 |
+
"eval_steps_per_second": 1.977,
|
| 1228 |
+
"step": 1160
|
| 1229 |
+
}
|
| 1230 |
+
],
|
| 1231 |
+
"logging_steps": 20,
|
| 1232 |
+
"max_steps": 4020,
|
| 1233 |
+
"num_input_tokens_seen": 0,
|
| 1234 |
+
"num_train_epochs": 10,
|
| 1235 |
+
"save_steps": 20,
|
| 1236 |
+
"stateful_callbacks": {
|
| 1237 |
+
"TrainerControl": {
|
| 1238 |
+
"args": {
|
| 1239 |
+
"should_epoch_stop": false,
|
| 1240 |
+
"should_evaluate": false,
|
| 1241 |
+
"should_log": false,
|
| 1242 |
+
"should_save": true,
|
| 1243 |
+
"should_training_stop": false
|
| 1244 |
+
},
|
| 1245 |
+
"attributes": {}
|
| 1246 |
+
}
|
| 1247 |
+
},
|
| 1248 |
+
"total_flos": 1.1472790102826803e+17,
|
| 1249 |
+
"train_batch_size": 4,
|
| 1250 |
+
"trial_name": null,
|
| 1251 |
+
"trial_params": null
|
| 1252 |
+
}
|